RRID:AB_2315602
DOI: 10.1016/j.immuni.2025.09.018
Resource: (Agilent Cat# A0082, RRID:AB_2315602)
Curator: @scibot
SciCrunch record: RRID:AB_2315602
RRID:AB_2315602
DOI: 10.1016/j.immuni.2025.09.018
Resource: (Agilent Cat# A0082, RRID:AB_2315602)
Curator: @scibot
SciCrunch record: RRID:AB_2315602
RRID:AB_10013485
DOI: 10.1016/j.immuni.2025.09.018
Resource: (Agilent Cat# M0725, RRID:AB_10013485)
Curator: @scibot
SciCrunch record: RRID:AB_10013485
RRID:AB_10976507
DOI: 10.1016/j.immuni.2025.09.018
Resource: (Abcam Cat# ab124716, RRID:AB_10976507)
Curator: @scibot
SciCrunch record: RRID:AB_10976507
RRID:AB_3717324
DOI: 10.1016/j.immuni.2025.09.018
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_3717324
RRID:AB_2335716
DOI: 10.1016/j.immuni.2025.09.018
Resource: (Thermo Fisher Scientific Cat# ICN55514, RRID:AB_2334520)
Curator: @scibot
SciCrunch record: RRID:AB_2334520
RRID:AB_2888308
DOI: 10.1016/j.immuni.2025.09.018
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_2888308
RRID:AB_3665072
DOI: 10.1016/j.immuni.2025.09.018
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_3665072
RRID:AB_10863040
DOI: 10.1016/j.immuni.2025.09.018
Resource: (Abcam Cat# ab109489, RRID:AB_10863040)
Curator: @scibot
SciCrunch record: RRID:AB_10863040
RRID:AB_2943181
DOI: 10.1016/j.immuni.2025.09.018
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_2943181
RRID:AB_2142367
DOI: 10.1016/j.immuni.2025.09.018
Resource: (Agilent Cat# M7240, RRID:AB_2142367)
Curator: @scibot
SciCrunch record: RRID:AB_2142367
RRID:AB_3657763
DOI: 10.1016/j.immuni.2025.09.018
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_3657763
RRID:AB_1310252
DOI: 10.1016/j.immuni.2025.09.018
Resource: (Abcam Cat# ab75810, RRID:AB_1310252)
Curator: @scibot
SciCrunch record: RRID:AB_1310252
RRID:AB_2894862
DOI: 10.1016/j.immuni.2025.09.018
Resource: (Abcam Cat# ab246518, RRID:AB_2894862)
Curator: @scibot
SciCrunch record: RRID:AB_2894862
RRID:AB_2537884
DOI: 10.1016/j.immuni.2025.09.018
Resource: (Thermo Fisher Scientific Cat# MA5-16365, RRID:AB_2537884)
Curator: @scibot
SciCrunch record: RRID:AB_2537884
RRID:AB_3717322
DOI: 10.1016/j.immuni.2025.09.018
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_3717322
RRID:AB_2927712
DOI: 10.1016/j.immuni.2025.09.018
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_2927712
RRID:AB_2924920
DOI: 10.1016/j.immuni.2025.09.018
Resource: (Abcam Cat# ab208586, RRID:AB_2924920)
Curator: @scibot
SciCrunch record: RRID:AB_2924920
RRID:AB_10013382
DOI: 10.1016/j.immuni.2025.09.018
Resource: (Agilent Cat# Z0334, RRID:AB_10013382)
Curator: @scibot
SciCrunch record: RRID:AB_10013382
RRID:AB_2075504
DOI: 10.1016/j.immuni.2025.09.018
Resource: (Abcam Cat# ab9514, RRID:AB_2075504)
Curator: @scibot
SciCrunch record: RRID:AB_2075504
RRID:AB_443437
DOI: 10.1016/j.immuni.2025.09.018
Resource: (Abcam Cat# ab16702, RRID:AB_443437)
Curator: @scibot
SciCrunch record: RRID:AB_443437
RRID:AB_2537853
DOI: 10.1016/j.immuni.2025.09.018
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_2537853
RRID:AB_2074844
DOI: 10.1016/j.immuni.2025.09.018
Resource: (Agilent Cat# M0876, RRID:AB_2074844)
Curator: @scibot
SciCrunch record: RRID:AB_2074844
RRID:AB_2282030
DOI: 10.1016/j.immuni.2025.09.018
Resource: (Agilent Cat# M0755, RRID:AB_2282030)
Curator: @scibot
SciCrunch record: RRID:AB_2282030
RRID:AB_3717323
DOI: 10.1016/j.immuni.2025.09.018
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_3717323
RRID:AB_2801511
DOI: 10.1016/j.immuni.2025.09.018
Resource: (Abcam Cat# ab214417, RRID:AB_2801511)
Curator: @scibot
SciCrunch record: RRID:AB_2801511
RRID:AB_3674755
DOI: 10.1016/j.immuni.2025.09.018
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_3674755
RRID:AB_2537857
DOI: 10.1016/j.immuni.2025.09.018
Resource: (Thermo Fisher Scientific Cat# MA5-16338, RRID:AB_2537857)
Curator: @scibot
SciCrunch record: RRID:AB_2537857
RRID:AB_2335677
DOI: 10.1016/j.immuni.2025.09.018
Resource: (Thermo Fisher Scientific Cat# ICN55463, RRID:AB_2334481)
Curator: @scibot
SciCrunch record: RRID:AB_2334481
RRID:AB_2223500
DOI: 10.1016/j.immuni.2025.09.018
Resource: (Agilent Cat# M0851, RRID:AB_2223500)
Curator: @scibot
SciCrunch record: RRID:AB_2223500
RRID:AB_2075537
DOI: 10.1016/j.immuni.2025.09.018
Resource: (Agilent Cat# M7103, RRID:AB_2075537)
Curator: @scibot
SciCrunch record: RRID:AB_2075537
RRID:CVCL_0547
DOI: 10.1016/j.ijbiomac.2025.148422
Resource: (BCRC Cat# 60343, RRID:CVCL_0547)
Curator: @scibot
SciCrunch record: RRID:CVCL_0547
RRID:CVCL_0063
DOI: 10.1016/j.ijbiomac.2025.148422
Resource: (RRID:CVCL_0063)
Curator: @scibot
SciCrunch record: RRID:CVCL_0063
RRID:CVCL_0546
DOI: 10.1016/j.ijbiomac.2025.148422
Resource: (KCB Cat# KCB 200848YJ, RRID:CVCL_0546)
Curator: @scibot
SciCrunch record: RRID:CVCL_0546
RRID:CVCL_0460
DOI: 10.1016/j.ijbiomac.2025.148422
Resource: (RRID:CVCL_0460)
Curator: @scibot
SciCrunch record: RRID:CVCL_0460
RRID:CVCL_L929
DOI: 10.1016/j.ijbiomac.2025.148397
Resource: None
Curator: @scibot
SciCrunch record: RRID:CVCL_L929
AB_777178
DOI: 10.1016/j.devcel.2025.09.018
Resource: (Abcam Cat# ab47308, RRID:AB_777178)
Curator: @scibot
SciCrunch record: RRID:AB_777178
RRID:AB_2340626
DOI: 10.1016/j.devcel.2025.09.018
Resource: (Jackson ImmunoResearch Labs Cat# 711-607-003, RRID:AB_2340626)
Curator: @scibot
SciCrunch record: RRID:AB_2340626
RRID:AB_143165
DOI: 10.1016/j.devcel.2025.09.018
Resource: (Thermo Fisher Scientific Cat# A-11008, RRID:AB_143165)
Curator: @scibot
SciCrunch record: RRID:AB_143165
RRID:AB_2534102
DOI: 10.1016/j.devcel.2025.09.018
Resource: (Thermo Fisher Scientific Cat# A-11055, RRID:AB_2534102)
Curator: @scibot
SciCrunch record: RRID:AB_2534102
RRID:AB_2535795
DOI: 10.1016/j.devcel.2025.09.018
Resource: (Thermo Fisher Scientific Cat# A-21209, RRID:AB_2535795)
Curator: @scibot
SciCrunch record: RRID:AB_2535795
RRID:AB_141930
DOI: 10.1016/j.devcel.2025.09.018
Resource: (Molecular Probes Cat# A-11076, RRID:AB_141930)
Curator: @scibot
SciCrunch record: RRID:AB_141930
RRID:AB_162542
DOI: 10.1016/j.devcel.2025.09.018
Resource: (Molecular Probes Cat# A-31571, RRID:AB_162542)
Curator: @scibot
SciCrunch record: RRID:AB_162542
RRID:AB_2161028
DOI: 10.1016/j.devcel.2025.09.018
Resource: (R and D Systems Cat# AF3628, RRID:AB_2161028)
Curator: @scibot
SciCrunch record: RRID:AB_2161028
RRID:AB_2271061
DOI: 10.1016/j.devcel.2025.09.018
Resource: (Santa Cruz Biotechnology Cat# sc-74556, RRID:AB_2271061)
Curator: @scibot
SciCrunch record: RRID:AB_2271061
RRID:AB_10011794
DOI: 10.1016/j.devcel.2025.09.018
Resource: (Novus Cat# NBP1-49672, RRID:AB_10011794)
Curator: @scibot
SciCrunch record: RRID:AB_10011794
RRID:AB_2107329
DOI: 10.1016/j.devcel.2025.09.018
Resource: (Millipore Cat# AB932, RRID:AB_2107329)
Curator: @scibot
SciCrunch record: RRID:AB_2107329
RRID:AB_2170716
DOI: 10.1016/j.devcel.2025.09.018
Resource: (R and D Systems Cat# AF2727, RRID:AB_2170716)
Curator: @scibot
SciCrunch record: RRID:AB_2170716
RRID:AB_2255626
DOI: 10.1016/j.devcel.2025.09.018
Resource: (DSHB Cat# GN-ID4, RRID:AB_2255626)
Curator: @scibot
SciCrunch record: RRID:AB_2255626
RRID:AB_3083712
DOI: 10.1016/j.devcel.2025.09.018
Resource: (R and D Systems Cat# MAB83771, RRID:AB_3083712)
Curator: @scibot
SciCrunch record: RRID:AB_3083712
RRID:AB_2536183
DOI: 10.1016/j.devcel.2025.09.018
Resource: (Thermo Fisher Scientific Cat# A-31573, RRID:AB_2536183)
Curator: @scibot
SciCrunch record: RRID:AB_2536183
RRID:AB_2239761
DOI: 10.1016/j.devcel.2025.09.018
Resource: (Millipore Cat# AB5535, RRID:AB_2239761)
Curator: @scibot
SciCrunch record: RRID:AB_2239761
RRID:AB_2716792
DOI: 10.1016/j.devcel.2025.09.018
Resource: (BD Biosciences Cat# 563023, RRID:AB_2716792)
Curator: @scibot
SciCrunch record: RRID:AB_2716792
RRID:AB_2739382
DOI: 10.1016/j.devcel.2025.09.018
Resource: (BD Biosciences Cat# 565860, RRID:AB_2739382)
Curator: @scibot
SciCrunch record: RRID:AB_2739382
RRID:AB_10716057
DOI: 10.1016/j.devcel.2025.09.018
Resource: (BD Biosciences Cat# 561589, RRID:AB_10716057)
Curator: @scibot
SciCrunch record: RRID:AB_10716057
RRID:AB_2739371
DOI: 10.1016/j.devcel.2025.09.018
Resource: (BD Biosciences Cat# 565831, RRID:AB_2739371)
Curator: @scibot
SciCrunch record: RRID:AB_2739371
RRID:AB_10893402
DOI: 10.1016/j.devcel.2025.09.018
Resource: (BD Biosciences Cat# 562205, RRID:AB_10893402)
Curator: @scibot
SciCrunch record: RRID:AB_10893402
RRID:AB_355257
DOI: 10.1016/j.devcel.2025.09.018
Resource: (R and D Systems Cat# AF2419, RRID:AB_355257)
Curator: @scibot
SciCrunch record: RRID:AB_355257
RRID:AB_314612
DOI: 10.1016/j.devcel.2025.09.018
Resource: (BioLegend Cat# 306506, RRID:AB_314612)
Curator: @scibot
SciCrunch record: RRID:AB_314612
RRID:AB_756082
DOI: 10.1016/j.devcel.2025.09.018
Resource: (BioLegend Cat# 324208, RRID:AB_756082)
Curator: @scibot
SciCrunch record: RRID:AB_756082
RRID:AB_314985
DOI: 10.1016/j.devcel.2025.09.018
Resource: (BioLegend Cat# 313206, RRID:AB_314985)
Curator: @scibot
SciCrunch record: RRID:AB_314985
RRID:AB_2684575
DOI: 10.1016/j.devcel.2025.09.017
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_2684575
plasmid_60820
DOI: 10.1016/j.devcel.2025.09.017
Resource: RRID:Addgene_60820
Curator: @scibot
SciCrunch record: RRID:Addgene_60820
RRID:AB_2685415
DOI: 10.1016/j.devcel.2025.09.017
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_2685415
RRID:AB_10601240
DOI: 10.1016/j.devcel.2025.09.017
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_10601240
RRID:AB_2223041
DOI: 10.1016/j.devcel.2025.09.017
Resource: (Millipore Cat# MAB1501, RRID:AB_2223041)
Curator: @scibot
SciCrunch record: RRID:AB_2223041
RRID:AB_2782993
DOI: 10.1016/j.devcel.2025.09.017
Resource: (Abcam Cat# ab150076, RRID:AB_2782993)
Curator: @scibot
SciCrunch record: RRID:AB_2782993
RRID:AB_300798
DOI: 10.1016/j.devcel.2025.09.017
Resource: (Abcam Cat# ab13970, RRID:AB_300798)
Curator: @scibot
SciCrunch record: RRID:AB_300798
RRID:AB_11042881
DOI: 10.1016/j.devcel.2025.09.017
Resource: (Proteintech Cat# 50430-2-AP, RRID:AB_11042881)
Curator: @scibot
SciCrunch record: RRID:AB_11042881
RRID:AB_443209
DOI: 10.1016/j.devcel.2025.09.017
Resource: (Abcam Cat# ab15580, RRID:AB_443209)
Curator: @scibot
SciCrunch record: RRID:AB_443209
RRID:AB_1139472
DOI: 10.1016/j.devcel.2025.09.017
Resource: (Abcam Cat# ab63507, RRID:AB_1139472)
Curator: @scibot
SciCrunch record: RRID:AB_1139472
RRID:AB_2722569
DOI: 10.1016/j.devcel.2025.09.017
Resource: (Active Motif Cat# 39134, RRID:AB_2722569)
Curator: @scibot
SciCrunch record: RRID:AB_2722569
RRID:AB_306327
DOI: 10.1016/j.devcel.2025.09.017
Resource: (Abcam Cat# ab817, RRID:AB_306327)
Curator: @scibot
SciCrunch record: RRID:AB_306327
RRID:AB_1031062
DOI: 10.1016/j.devcel.2025.09.017
Resource: (Cell Signaling Technology Cat# 2729, RRID:AB_1031062)
Curator: @scibot
SciCrunch record: RRID:AB_1031062
RRID:AB_303395
DOI: 10.1016/j.devcel.2025.09.017
Resource: (Abcam Cat# ab290, RRID:AB_303395)
Curator: @scibot
SciCrunch record: RRID:AB_303395
RRID:AB_2099233
DOI: 10.1016/j.devcel.2025.09.016
Resource: (Cell Signaling Technology Cat# 7074, RRID:AB_2099233)
Curator: @scibot
SciCrunch record: RRID:AB_2099233
RRID:AB_2800177
DOI: 10.1016/j.devcel.2025.09.016
Resource: (Cell Signaling Technology Cat# 92043, RRID:AB_2800177)
Curator: @scibot
SciCrunch record: RRID:AB_2800177
RRID:AB_2572291
DOI: 10.1016/j.devcel.2025.09.016
Resource: (Cell Signaling Technology Cat# 14793, RRID:AB_2572291)
Curator: @scibot
SciCrunch record: RRID:AB_2572291
RRID:AB_330924
DOI: 10.1016/j.devcel.2025.09.016
Resource: (Cell Signaling Technology Cat# 7076, RRID:AB_330924)
Curator: @scibot
SciCrunch record: RRID:AB_330924
RRID:AB_2737028
DOI: 10.1016/j.devcel.2025.09.016
Resource: (Active Motif Cat# 61489, RRID:AB_2737028)
Curator: @scibot
SciCrunch record: RRID:AB_2737028
RRID:AB_331277
DOI: 10.1016/j.devcel.2025.09.016
Resource: (Cell Signaling Technology Cat# 9197, RRID:AB_331277)
Curator: @scibot
SciCrunch record: RRID:AB_331277
RRID:AB_1119692
DOI: 10.1016/j.devcel.2025.09.016
Resource: (Santa Cruz Biotechnology Cat# sc-81202, RRID:AB_1119692)
Curator: @scibot
SciCrunch record: RRID:AB_1119692
RRID:AB_1125727
DOI: 10.1016/j.devcel.2025.09.016
Resource: (Santa Cruz Biotechnology Cat# sc-81486, RRID:AB_1125727)
Curator: @scibot
SciCrunch record: RRID:AB_1125727
RRID:AB_2616020
DOI: 10.1016/j.devcel.2025.09.016
Resource: (Cell Signaling Technology Cat# 7389, RRID:AB_2616020)
Curator: @scibot
SciCrunch record: RRID:AB_2616020
RRID:AB_2799901
DOI: 10.1016/j.devcel.2025.09.016
Resource: (Cell Signaling Technology Cat# 77510, RRID:AB_2799901)
Curator: @scibot
SciCrunch record: RRID:AB_2799901
RRID:AB_561053
DOI: 10.1016/j.devcel.2025.09.016
Resource: (Cell Signaling Technology Cat# 2118, RRID:AB_561053)
Curator: @scibot
SciCrunch record: RRID:AB_561053
RRID:AB_2242334
DOI: 10.1016/j.devcel.2025.09.016
Resource: (Cell Signaling Technology Cat# 3700, RRID:AB_2242334)
Curator: @scibot
SciCrunch record: RRID:AB_2242334
RRID:AB_2561044
DOI: 10.1016/j.devcel.2025.09.016
Resource: (Cell Signaling Technology Cat# 9198, RRID:AB_2561044)
Curator: @scibot
SciCrunch record: RRID:AB_2561044
Jackson Laboratory Cat_000664
DOI: 10.1016/j.devcel.2025.09.016
Resource: None
Curator: @areedewitt04
SciCrunch record: RRID:IMSR_JAX:000664
JAX:007914
DOI: 10.1016/j.crmeth.2025.101208
Resource: (IMSR Cat# JAX_007914,RRID:IMSR_JAX:007914)
Curator: @scibot
SciCrunch record: RRID:IMSR_JAX:007914
JAX:016261
DOI: 10.1016/j.crmeth.2025.101208
Resource: (IMSR Cat# JAX_016261,RRID:IMSR_JAX:016261)
Curator: @scibot
SciCrunch record: RRID:IMSR_JAX:016261
JAX:000664
DOI: 10.1016/j.crmeth.2025.101208
Resource: RRID:IMSR_JAX:000664
Curator: @scibot
SciCrunch record: RRID:IMSR_JAX:000664
SCR_002285
DOI: 10.1016/j.crmeth.2025.101208
Resource: Fiji (RRID:SCR_002285)
Curator: @scibot
SciCrunch record: RRID:SCR_002285
RRID:SCR_013672
DOI: 10.1016/j.crmeth.2025.101208
Resource: ZEISS ZEN Microscopy Software (RRID:SCR_013672)
Curator: @scibot
SciCrunch record: RRID:SCR_013672
RRID:SCR_002798
DOI: 10.1016/j.crmeth.2025.101208
Resource: GraphPad Prism (RRID:SCR_002798)
Curator: @scibot
SciCrunch record: RRID:SCR_002798
RRID:CVCL_4358
DOI: 10.1016/j.crmeth.2025.101208
Resource: (IZSLER Cat# BS TCL 216, RRID:CVCL_4358)
Curator: @scibot
SciCrunch record: RRID:CVCL_4358
RRID:SCR_007416
DOI: 10.1016/j.crmeth.2025.101208
Resource: Allen Human Brain Atlas (RRID:SCR_007416)
Curator: @scibot
SciCrunch record: RRID:SCR_007416
RRID:SCR_007370
DOI: 10.1016/j.crmeth.2025.101208
Resource: Imaris (RRID:SCR_007370)
Curator: @scibot
SciCrunch record: RRID:SCR_007370
RRID:CVCL_0393
DOI: 10.1016/j.crmeth.2025.101208
Resource: (ATCC Cat# CRL-2611, RRID:CVCL_0393)
Curator: @scibot
SciCrunch record: RRID:CVCL_0393
RRID:AB_10854564
DOI: 10.1016/j.crmeth.2025.101208
Resource: (Thermo Fisher Scientific Cat# 14-5698-82, RRID:AB_10854564)
Curator: @scibot
SciCrunch record: RRID:AB_10854564
RRID:AB_2534077
DOI: 10.1016/j.crmeth.2025.101208
Resource: (Thermo Fisher Scientific Cat# A-11010, RRID:AB_2534077)
Curator: @scibot
SciCrunch record: RRID:AB_2534077
RRID:AB_390204
DOI: 10.1016/j.crmeth.2025.101208
Resource: (Millipore Cat# AB152, RRID:AB_390204)
Curator: @scibot
SciCrunch record: RRID:AB_390204
RRID:AB_2574362
DOI: 10.1016/j.crmeth.2025.101208
Resource: (Thermo Fisher Scientific Cat# 50-9760-82, RRID:AB_2574362)
Curator: @scibot
SciCrunch record: RRID:AB_2574362
RRID:AB_10581494
DOI: 10.1016/j.crmeth.2025.101201
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_10581494
RRID:AB_2861289
DOI: 10.1016/j.crmeth.2025.101201
Resource: (BIOCARE MEDICAL Cat# 3099, RRID:AB_2861289)
Curator: @scibot
SciCrunch record: RRID:AB_2861289
RRID:AB_2894718
DOI: 10.1016/j.crmeth.2025.101201
Resource: (Roche Cat# 07560389001, RRID:AB_2894718)
Curator: @scibot
SciCrunch record: RRID:AB_2894718
RRID:IMSR_JAX:002101
DOI: 10.1016/j.celrep.2025.116439
Resource: RRID:IMSR_JAX:002101
Curator: @scibot
SciCrunch record: RRID:IMSR_JAX:002101
RRID:IMSR_JAX:032435
DOI: 10.1016/j.celrep.2025.116439
Resource: (IMSR Cat# JAX_032435,RRID:IMSR_JAX:032435)
Curator: @scibot
SciCrunch record: RRID:IMSR_JAX:032435
RRID:IMSR_JAX:002674
DOI: 10.1016/j.celrep.2025.116439
Resource: None
Curator: @scibot
SciCrunch record: RRID:IMSR_JAX:002674
RRID:AB_2762371
DOI: 10.1016/j.celrep.2025.116438
Resource: (Thermo Fisher Scientific Cat# 712137, RRID:AB_2762371)
Curator: @scibot
SciCrunch record: RRID:AB_2762371
RRID:AB_2882339
DOI: 10.1016/j.celrep.2025.116438
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_2882339
RRID:AB_3714704
DOI: 10.1016/j.celrep.2025.116438
Resource: (Abbkine Cat# ABL1020, RRID:AB_3714704)
Curator: @scibot
SciCrunch record: RRID:AB_3714704
RRID:AB_2882450
DOI: 10.1016/j.celrep.2025.116438
Resource: (Proteintech Cat# 67153-1-Ig, RRID:AB_2882450)
Curator: @scibot
SciCrunch record: RRID:AB_2882450
RRID:AB_2092506
DOI: 10.1016/j.celrep.2025.116438
Resource: (Proteintech Cat# 17721-1-AP, RRID:AB_2092506)
Curator: @scibot
SciCrunch record: RRID:AB_2092506
RRID:AB_439701
DOI: 10.1016/j.celrep.2025.116438
Resource: (Sigma-Aldrich Cat# F4049, RRID:AB_439701)
Curator: @scibot
SciCrunch record: RRID:AB_439701
RRID:AB_2687948
DOI: 10.1016/j.celrep.2025.116438
Resource: (Abcam Cat# ab150115, RRID:AB_2687948)
Curator: @scibot
SciCrunch record: RRID:AB_2687948
RRID:AB_1640564
DOI: 10.1016/j.celrep.2025.116438
Resource: (Abcam Cat# ab81299, RRID:AB_1640564)
Curator: @scibot
SciCrunch record: RRID:AB_1640564
RRID:AB_2238624
DOI: 10.1016/j.celrep.2025.116438
Resource: (Proteintech Cat# 15606-1-AP, RRID:AB_2238624)
Curator: @scibot
SciCrunch record: RRID:AB_2238624
RRID:AB_2861387
DOI: 10.1016/j.celrep.2025.116438
Resource: (Millipore Cat# MABE1095, RRID:AB_2861387)
Curator: @scibot
SciCrunch record: RRID:AB_2861387
RRID:AB_2279214
DOI: 10.1016/j.celrep.2025.116438
Resource: (Synaptic Systems Cat# 202 003, RRID:AB_2279214)
Curator: @scibot
SciCrunch record: RRID:AB_2279214
AB_2534017
DOI: 10.1016/j.celrep.2025.116434
Resource: (Thermo Fisher Scientific Cat# A10042, RRID:AB_2534017)
Curator: @scibot
SciCrunch record: RRID:AB_2534017
RRID:MGI:3837408
DOI: 10.1016/j.celrep.2025.116434
Resource: None
Curator: @scibot
SciCrunch record: RRID:MGI:3837408
RRID:AB_141709
DOI: 10.1016/j.celrep.2025.116434
Resource: (Thermo Fisher Scientific Cat# A-21208, RRID:AB_2535794)
Curator: @scibot
SciCrunch record: RRID:AB_2535794
RRID:AB_449517
DOI: 10.1016/j.celrep.2025.116434
Resource: (Abcam Cat# ab6336, RRID:AB_449517)
Curator: @scibot
SciCrunch record: RRID:AB_449517
RRID:AB_444319
DOI: 10.1016/j.celrep.2025.116434
Resource: (Abcam Cat# ab18207, RRID:AB_444319)
Curator: @scibot
SciCrunch record: RRID:AB_444319
RRID:AB_2534137
DOI: 10.1016/j.celrep.2025.116427
Resource: (Thermo Fisher Scientific Cat# A-11131, RRID:AB_2534137)
Curator: @scibot
SciCrunch record: RRID:AB_2534137
RRID:AB_228341
DOI: 10.1016/j.celrep.2025.116427
Resource: (Thermo Fisher Scientific Cat# 31460, RRID:AB_228341)
Curator: @scibot
SciCrunch record: RRID:AB_228341
RRID:AB_259965
DOI: 10.1016/j.celrep.2025.116427
Resource: (Sigma-Aldrich Cat# G7781, RRID:AB_259965)
Curator: @scibot
SciCrunch record: RRID:AB_259965
RRID:AB_2715503
DOI: 10.1016/j.cbi.2025.111788
Resource: (Cell Signaling Technology Cat# 12242, RRID:AB_2715503)
Curator: @scibot
SciCrunch record: RRID:AB_2715503
RRID:AB_823586
DOI: 10.1016/j.cbi.2025.111788
Resource: (Cell Signaling Technology Cat# 2947, RRID:AB_823586)
Curator: @scibot
SciCrunch record: RRID:AB_823586
RRID:AB_1841064
DOI: 10.1016/j.cbi.2025.111788
Resource: (Sigma-Aldrich Cat# P0067, RRID:AB_1841064)
Curator: @scibot
SciCrunch record: RRID:AB_1841064
RRID:CVCL_0130
DOI: 10.1016/j.cbi.2025.111788
Resource: (NCBI_Iran Cat# C600, RRID:CVCL_0130)
Curator: @scibot
SciCrunch record: RRID:CVCL_0130
RRID:AB_2839417
DOI: 10.1016/j.cbi.2025.111788
Resource: (Affinity Biosciences Cat# T0022, RRID:AB_2839417)
Curator: @scibot
SciCrunch record: RRID:AB_2839417
RRID:AB_330331
DOI: 10.1016/j.cbi.2025.111788
Resource: (Cell Signaling Technology Cat# 2532, RRID:AB_330331)
Curator: @scibot
SciCrunch record: RRID:AB_330331
RRID:AB_331250
DOI: 10.1016/j.cbi.2025.111788
Resource: (Cell Signaling Technology Cat# 2535, RRID:AB_331250)
Curator: @scibot
SciCrunch record: RRID:AB_331250
RRID:AB_796155
DOI: 10.1016/j.cbi.2025.111788
Resource: (Sigma-Aldrich Cat# L7543, RRID:AB_796155)
Curator: @scibot
SciCrunch record: RRID:AB_796155
RRID:AB_2833041
DOI: 10.1016/j.cbi.2025.111788
Resource: (Affinity Biosciences Cat# T0004, RRID:AB_2833041)
Curator: @scibot
SciCrunch record: RRID:AB_2833041
RRID:CVCL_G654
DOI: 10.1016/j.biopha.2025.118657
Resource: (ATCC Cat# CRL-2700, RRID:CVCL_G654)
Curator: @scibot
SciCrunch record: RRID:CVCL_G654
RRID:CVCL_0063
DOI: 10.1016/j.biopha.2025.118657
Resource: (RRID:CVCL_0063)
Curator: @scibot
SciCrunch record: RRID:CVCL_0063
RRID:CVCL_0609
DOI: 10.1016/j.biopha.2025.118657
Resource: (ATCC Cat# HTB-55, RRID:CVCL_0609)
Curator: @scibot
SciCrunch record: RRID:CVCL_0609
RRID:CVCL_0574
DOI: 10.1016/j.biopha.2025.118657
Resource: (IZSLER Cat# BS CL 87, RRID:CVCL_0574)
Curator: @scibot
SciCrunch record: RRID:CVCL_0574
RRID:SCR_018883
DOI: 10.1016/j.actbio.2025.10.031
Resource: Virginia University School of Medicine Genome Analysis and Technology Core Facility (RRID:SCR_018883)
Curator: @scibot
SciCrunch record: RRID:SCR_018883
RRID:SCR_018736
DOI: 10.1016/j.actbio.2025.10.031
Resource: Virginia University School of Medicine Advanced Microscopy Core Facility (RRID:SCR_018736)
Curator: @scibot
SciCrunch record: RRID:SCR_018736
Jackson Laboratory Cat_003715
DOI: 10.1016/j.stem.2025.09.009
Resource: None
Curator: @areedewitt04
SciCrunch record: RRID:IMSR_JAX:003715
plasmid_9882642
DOI: 10.1016/j.isci.2025.113697
Resource: None
Curator: @areedewitt04
SciCrunch record: RRID:Addgene_98826
share via guest@cryptpad
Start the conversation over there
<svg viewBox="0 0 1100 500" width="670" height="370" version="1.1" xmlns="http://www.w3.org/2000/svg"><rect width="2000" height="1000" fill="#FFFFFF"></rect><g transform="translate(304,295)"><text text-anchor="middle" transform="translate(-88, -106)" style="font-size: 70px; user-select: none; cursor: default; font-family: Lato; fill: rgb(0, 150, 210);">hyperpost</text><text text-anchor="middle" transform="translate(133, -91)" style="font-size: 70px; user-select: none; cursor: default; font-family: Lato; fill: rgb(0, 150, 210);">link</text><text text-anchor="middle" transform="translate(7, 18)" style="font-size: 70px; user-select: none; cursor: default; font-family: Lato; fill: rgb(0, 150, 210);">peergos</text><text text-anchor="middle" transform="translate(-26, 73)" style="font-size: 56.5px; user-select: none; cursor: default; font-family: Lato; fill: rgb(0, 150, 210);">add</text><text text-anchor="middle" transform="translate(94, -41)" style="font-size: 56.5px; user-select: none; cursor: default; font-family: Lato; fill: rgb(0, 150, 210);">path</text><text text-anchor="middle" transform="translate(97, 138)" style="font-size: 43px; user-select: none; cursor: default; font-family: Lato; fill: rgb(76, 40, 130);">gyuri</text><text text-anchor="middle" transform="translate(-122, 62)" style="font-size: 43px; user-select: none; cursor: default; font-family: Lato; fill: rgb(76, 40, 130);">view</text><text text-anchor="middle" transform="translate(-43, -154)" style="font-size: 43px; user-select: none; cursor: default; font-family: Lato; fill: rgb(76, 40, 130);">sandbox</text><text text-anchor="middle" transform="translate(-8, -41)" style="font-size: 29.5px; user-select: none; cursor: default; font-family: Lato; fill: rgb(76, 40, 130);">week</text><text text-anchor="middle" transform="translate(-120, -68)" style="font-size: 29.5px; user-select: none; cursor: default; font-family: Lato; fill: rgb(0, 236, 183);">hypothes</text><text text-anchor="middle" transform="translate(15, 98)" style="font-size: 29.5px; user-select: none; cursor: default; font-family: Lato; fill: rgb(0, 236, 183);">copy</text><text text-anchor="middle" transform="translate(-127, -33)" style="font-size: 29.5px; user-select: none; cursor: default; font-family: Lato; fill: rgb(0, 236, 183);">appropriate</text><text text-anchor="middle" transform="translate(-13, -75)" style="font-size: 29.5px; user-select: none; cursor: default; font-family: Lato; fill: rgb(0, 236, 183);">net</text><text text-anchor="middle" transform="translate(-160, -159)" style="font-size: 29.5px; user-select: none; cursor: default; font-family: Lato; fill: rgb(231, 33, 153);">url</text><text text-anchor="middle" transform="translate(-149, 9)" style="font-size: 29.5px; user-select: none; cursor: default; font-family: Lato; fill: rgb(231, 33, 153);">web</text><text text-anchor="middle" transform="translate(-53, 94)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(231, 33, 153);">antate</text><text text-anchor="middle" transform="translate(13, -191)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(231, 33, 153);">created</text><text text-anchor="middle" transform="translate(-101, -193)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(135, 105, 214);">methodology</text><text text-anchor="middle" transform="translate(169, -18)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(135, 105, 214);">human</text><text text-anchor="middle" transform="translate(-202, -67)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(135, 105, 214);">sis</text><text text-anchor="middle" transform="translate(79, -152)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(135, 105, 214);">one</text></g></svg>
<svg viewBox="100 100 1100 500" width="670" height="300" version="1.1" xmlns="http://www.w3.org/2000/svg"><rect width="1100" height="600" fill="#FFFFFF"></rect><g transform="translate(419,295)"><text text-anchor="middle" transform="translate(57, -102)" style="font-size: 70px; user-select: none; cursor: default; font-family: Lato; fill: rgb(0, 150, 210);">web</text><text text-anchor="middle" transform="translate(-55, -10)" style="font-size: 37.6px; user-select: none; cursor: default; font-family: Lato; fill: rgb(0, 150, 210);">save</text><text text-anchor="middle" transform="translate(-166, -27)" style="font-size: 37.6px; user-select: none; cursor: default; font-family: Lato; fill: rgb(0, 150, 210);">pages</text><text text-anchor="middle" transform="translate(58, -64)" style="font-size: 26.8px; user-select: none; cursor: default; font-family: Lato; fill: rgb(0, 150, 210);">folder</text><text text-anchor="middle" transform="translate(117, 49)" style="font-size: 26.8px; user-select: none; cursor: default; font-family: Lato; fill: rgb(0, 150, 210);">saved</text><text text-anchor="middle" transform="translate(-110, -111)" style="font-size: 26.8px; user-select: none; cursor: default; font-family: Lato; fill: rgb(0, 150, 210);">singlefile</text><text text-anchor="middle" transform="translate(-147, 91)" style="font-size: 26.8px; user-select: none; cursor: default; font-family: Lato; fill: rgb(0, 150, 210);">page</text><text text-anchor="middle" transform="translate(-29, -86)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(0, 150, 210);">gyuri's</text><text text-anchor="middle" transform="translate(-135, 30)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(0, 150, 210);">snarf</text><text text-anchor="middle" transform="translate(-209, 56)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(0, 150, 210);">week</text><text text-anchor="middle" transform="translate(-15, -56)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(76, 40, 130);">october</text><text text-anchor="middle" transform="translate(-145, 55)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(76, 40, 130);">links</text><text text-anchor="middle" transform="translate(29, 112)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(76, 40, 130);">view</text><text text-anchor="middle" transform="translate(-7, 141)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(76, 40, 130);">sandbox</text><text text-anchor="middle" transform="translate(117, 128)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(76, 40, 130);">purpose</text><text text-anchor="middle" transform="translate(-20, -149)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(76, 40, 130);">provide</text><text text-anchor="middle" transform="translate(48, -19)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(76, 40, 130);">space</text><text text-anchor="middle" transform="translate(-158, -75)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(76, 40, 130);">meta-reflective</text><text text-anchor="middle" transform="translate(140, -64)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(76, 40, 130);">discussion</text><text text-anchor="middle" transform="translate(154, -87)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(76, 40, 130);">dedicated</text><text text-anchor="middle" transform="translate(-92, 66)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(0, 236, 183);">snarfed</text><text text-anchor="middle" transform="translate(-154, -140)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(0, 236, 183);">copied</text><text text-anchor="middle" transform="translate(-79, -40)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(0, 236, 183);">without</text><text text-anchor="middle" transform="translate(84, -164)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(0, 236, 183);">explicit</text><text text-anchor="middle" transform="translate(-149, -3)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(0, 236, 183);">permission</text><text text-anchor="middle" transform="translate(169, 108)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(0, 236, 183);">private</text><text text-anchor="middle" transform="translate(-206, 95)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(0, 236, 183);">study</text><text text-anchor="middle" transform="translate(134, 87)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(0, 236, 183);">research</text><text text-anchor="middle" transform="translate(169, -113)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(0, 236, 183);">attributed</text><text text-anchor="middle" transform="translate(56, -43)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(0, 236, 183);">sharing</text><text text-anchor="middle" transform="translate(233, -93)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(231, 33, 153);">claiming</text><text text-anchor="middle" transform="translate(4, 8)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(231, 33, 153);">constitutin</text><text text-anchor="middle" transform="translate(-185, -99)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(231, 33, 153);">fair</text><text text-anchor="middle" transform="translate(36, -152)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(231, 33, 153);">use</text><text text-anchor="middle" transform="translate(166, 66)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(231, 33, 153);">usin</text><text text-anchor="middle" transform="translate(-102, 136)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(231, 33, 153);">browser</text><text text-anchor="middle" transform="translate(-65, 88)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(231, 33, 153);">extension</text><text text-anchor="middle" transform="translate(-44, -169)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(231, 33, 153);">designed</text><text text-anchor="middle" transform="translate(-226, -94)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(231, 33, 153);">form</text><text text-anchor="middle" transform="translate(-62, 117)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(231, 33, 153);">allows</text><text text-anchor="middle" transform="translate(-232, 2)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(135, 105, 214);">failthful</text><text text-anchor="middle" transform="translate(54, -185)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(135, 105, 214);">presentation</text><text text-anchor="middle" transform="translate(-203, 26)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(135, 105, 214);">looked</text><text text-anchor="middle" transform="translate(-198, -122)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(135, 105, 214);">time</text><text text-anchor="middle" transform="translate(184, 27)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(135, 105, 214);">saving</text><text text-anchor="middle" transform="translate(196, 139)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(135, 105, 214);">understand</text><text text-anchor="middle" transform="translate(-54, 28)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(135, 105, 214);">correctly</text><text text-anchor="middle" transform="translate(219, 95)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(135, 105, 214);">runs</text><text text-anchor="middle" transform="translate(149, -149)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(135, 105, 214);">jaacript</text><text text-anchor="middle" transform="translate(208, 6)" style="user-select: none; cursor: default; font-family: Lato; fill: rgb(135, 105, 214);">resultatnt</text></g></svg>
Emma Bowman. After Data Breach Exposes 530 Million, Facebook Says It Will Not Notify Users. NPR, April 2021. URL: https://www.npr.org/2021/04/09/986005820/after-data-breach-exposes-530-million-facebook-says-it-will-not-notify-users (visited on 2023-12-06).
I found the inclusion of Bowman’s article about the 530 million-user breach striking — it grounds the discussion of privacy in real, large-scale harm rather than abstract theory. From my experience, seeing such breaches makes the “privacy isn’t just about secrets, it’s about control and trust” line hit home.
Private message. November 2023. Page Version ID: 1185376021. URL: https://en.wikipedia.org/w/index.php?title=Private_message&oldid=1185376021 (visited on 2023-12-05).
This article outlines how direct messaging systems have evolved across social media platforms, but what stood out to me is few of these systems are truly private. Even when messages are labeled as direct or personal, they are still stored on centralized servers that companies can access for moderation, data analysis, or even advertising purposes. This connects directly to 9.1's discussion of privacy illusions. How private online communication is often just a matter of perception. It makes me question whether privacy online is ever absolute, or if it's always conditional on the platform's policies and profit motives.
This has great practical value as well; the ability to debug a full manipulation stack with repeatable deterministic simulations (even if they include randomness) is surprisingly rare in the field but hugely valuable.
Having worked with gazebo and ros, I can vouch for this! deterministic simulation is such an underrated feature until you've lost days to Heisenbugs
When we use social media platforms though, we at least partially give up some of our privacy.
I found how users often feel they’ve lost control over their data interesting — it reminds me of the moments when I accept a “Cookie/Privacy” pop-up without really reading it, then later wonder how much the platform knows about my interests.
For example, a social media application might offer us a way of “Private Messaging” [i1] (also called Direct Messaging) with another user. But in most cases those “private” messages are stored in the computers at those companies, and the company might have computer programs that automatically search through the messages, and people with the right permissions might be able to view them directly.
I find this section very relatable because it captures how fragile our sense of privacy really online. The example of private messaging makes me think about how I often assume my DMs are confidential, even though they are stored and possibly analyzes by the platform itself. What feels private to users is often just conveniently invisible. I think this blurring between private and public spaces is what makes digital privacy so psychologically complex. It's not only about hiding information but about controlling context and audience. The idea that company can read what I write to a friend reminds me that privacy online is less of a right and more of a temporary permission.
https://www.youtube.com/watch?v=1X7fZoDs9KU
https://hyp.is/go?url=https%3A%2F%2Fwww.youtube.com%2Fwatch%3Fv%3D1X7fZoDs9KU&group=world
Les extraits proviennent d'une transcription de la vidéo TED intitulée « Quel pays fait le plus de bien pour le monde ? » par Simon Anholt, qui a été traduite en français.
Anholt commence par aborder les défis et les paradoxes de la mondialisation, soulignant comment des problèmes autrefois locaux sont désormais des menaces mondiales, comme les épidémies et les crises économiques.
Il attribue la lenteur des progrès dans la résolution de ces problèmes mondiaux au fait que les pays restent organisés en quelque 200 États-nations, dont les gouvernements sont centrés sur leurs propres intérêts nationaux plutôt que sur la coopération mondiale.
Anholt présente ensuite sa recherche, l'Indice des marques nationales, qui a révélé que les gens admirent les pays non pas pour leur richesse ou leur succès, mais parce qu'ils sont perçus comme « bons », c'est-à-dire qu'ils contribuent positivement au reste du monde.
Cette découverte l'a conduit à créer l'Indice des Bons Pays, qui mesure la contribution de chaque pays à l'humanité, avec l'Irlande classée au premier rang au moment de l'étude.
Finalement, Anholt exhorte le public à intégrer le mot « bon » (au sens de non-égoïste) dans le discours politique pour encourager les nations à adopter une approche plus altruiste et collaborative.
Analyse du "Bon Pays" : Mondialisation, Coopération et Intérêt National
https://hyp.is/go?url=https%3A%2F%2Findex.goodcountry.org%2F&group=world
Ce document de synthèse analyse les thèses centrales présentées par Simon Anholt concernant les défis de la mondialisation et la nécessité d'une nouvelle approche de la gouvernance mondiale.
Le problème fondamental identifié est un décalage critique : alors que les problèmes les plus urgents de l'humanité (changement climatique, pandémies, crises économiques) sont mondialisés, les systèmes de gouvernance restent ancrés dans des cadres nationaux égoïstes.
Trois obstacles majeurs à la coopération internationale sont identifiés : la demande des électeurs pour des politiques nationalistes, une forme de "psychopathie culturelle" qui limite l'empathie envers les étrangers, et la fausse croyance des dirigeants que les agendas nationaux et internationaux sont incompatibles.
La solution proposée repose sur une découverte issue d'une analyse de données à grande échelle sur la perception des pays (l'Indice des Marques Nationales). Cette recherche révèle que les pays les plus admirés ne sont pas les plus riches ou les plus puissants, mais ceux perçus comme "bons" – c'est-à-dire ceux qui contribuent de manière significative au bien commun de l'humanité.
Cette découverte lie directement la "bonté" d'un pays à son "intérêt personnel", car une réputation positive attire investissements, tourisme et talents, rendant la collaboration internationale un levier de compétitivité nationale.
Pour matérialiser ce concept, Anholt a créé "l'Indice des Bons Pays", qui mesure la contribution de chaque nation à l'humanité.
L'Irlande se classe au premier rang, démontrant qu'un pays peut honorer ses devoirs internationaux tout en gérant ses propres défis économiques.
L'appel à l'action final est d'intégrer le terme "bon" (défini comme le contraire d'égoïste) dans le discours public et politique, afin de créer une pression citoyenne pour que les gouvernements adoptent des politiques plus collaboratives et tournées vers l'extérieur.
La mondialisation a profondément interconnecté le monde, créant un système où des événements locaux peuvent avoir des répercussions mondiales quasi instantanées. Des exemples frappants illustrent cette réalité :
• Sanitaire : "Il y a 20 ou 30 ans, si un poulet attrapait froid, éternuait et mourait dans un petit village d'Extrême-Orient, c'était tragique pour le poulet [...] mais c'était peu probable qu'on ait peur d'une pandémie mondiale".
• Économique : "si une banque américaine prêtait trop d'argent à des clients non solvables et que la banque faisait faillite, c'était néfaste [...] mais nous ne pensions pas que ça amènerait un effondrement du système économique pendant presque dix ans."
Cette interconnexion a apporté des bénéfices, comme le succès des Objectifs du Millénaire, prouvant que "l'espèce humaine peut arriver à d'extraordinaires progrès en se montrant unie et persévérante".
Cependant, la mondialisation a également amplifié les problèmes : réchauffement climatique, terrorisme, épidémies, trafic de drogue, et bien d'autres.
Le problème central est que l'humanité n'a pas adapté ses structures de gouvernance à cette nouvelle réalité.
L'organisation mondiale est toujours fragmentée en environ 200 États-nations dont les gouvernements sont programmés pour se concentrer quasi exclusivement sur leurs intérêts nationaux.
Citation clé : "Il faut que nous arrivions à nous reprendre et trouver comment améliorer la mondialisation des solutions pour éviter de devenir une espèce victime de la mondialisation des problèmes."
Simon Anholt identifie trois raisons principales qui expliquent la lenteur des progrès sur les enjeux mondiaux et la persistance de l'approche nationaliste.
La première raison est que les citoyens eux-mêmes exigent de leurs gouvernements une focalisation interne.
En élisant ou en tolérant des gouvernements, le message envoyé est clair : la priorité est la prospérité, la croissance, la compétitivité et la justice à l'intérieur des frontières nationales.
Les politiciens, en regardant "dans un microscope" plutôt que "dans un télescope", ne font que répondre à cette demande.
Le deuxième obstacle est un biais psychologique collectif qu'Anholt nomme la "psychopathie culturelle".
Il s'agit d'un manque de capacité à ressentir une véritable empathie pour les personnes qui sont culturellement différentes.
• L'empathie fonctionne bien avec ceux qui "nous ressemblent, marchent, parlent, mangent, prient et s'habillent comme nous".
• En revanche, les autres, ceux qui sont différents, sont souvent perçus comme des "personnages en carton", des figures bidimensionnelles plutôt que des êtres humains complexes.
Ce manque d'empathie à grande échelle empêche une véritable solidarité mondiale.
Le troisième obstacle est la croyance, particulièrement ancrée chez les dirigeants, que les agendas nationaux et internationaux sont mutuellement exclusifs. Anholt qualifie cette idée de "grand n'importe quoi".
Fort de son expérience de conseiller politique auprès de nombreux gouvernements, il affirme n'avoir jamais vu "un seul problème national qui ne pouvait être résolu de façon plus inventive, plus efficace et plus rapide qu'en le traitant comme un problème international".
Pour surmonter ces obstacles et la résistance naturelle de l'être humain au changement, il est nécessaire de démontrer qu'un comportement plus collaboratif sert l'intérêt personnel des nations. C'est le cœur de la découverte d'Anholt.
En 2005, Anholt a lancé l'Indice des Marques Nationales, une étude à très grande échelle recueillant les perceptions du public mondial sur les différents pays.
Cette base de données de 200 milliards de points de données a révélé un fait économique crucial :
• Les pays dépendent "énormément de leurs réputations afin de survivre et de prospérer dans le monde".
• Une bonne image (ex : Allemagne, Suède, Suisse) facilite tout : tourisme, investissements, exportation.
• Une mauvaise image rend tout "difficile et [...] cher".
En interrogeant cette base de données pour comprendre pourquoi certains pays sont plus admirés que d'autres, la réponse fut surprenante.
Ce n'est ni la richesse, ni la puissance, ni la modernité qui est le facteur principal.
Citation clé : "les pays que nous préférons sont les bons pays. [...] nous admirons surtout un pays parce qu'il est bon."
Un "bon pays" est défini comme un pays qui "contribue au monde dans lequel nous vivons", le rendant "plus sûr, meilleur, plus riche ou plus juste".
Cette découverte crée un lien direct et puissant entre l'altruisme et l'égoïsme : pour réussir économiquement (servir son intérêt national), un pays doit "faire le bien" et contribuer à l'humanité.
"Plus vous collaborez, plus vous devenez compétitif."
Pour concrétiser cette idée, Anholt et son équipe ont développé l'Indice des Bons Pays ("The Good Country Index").
• Objectif : Mesurer la contribution exacte de chaque pays, non pas à ses propres habitants, mais au reste de l'humanité.
• Définition de "Bon" : Le terme n'a pas une connotation morale ("bon" vs "mauvais"), mais est utilisé comme le contraire de "égoïste".
Un "bon" pays est un pays qui se préoccupe des intérêts de tous.
Les résultats de l'indice offrent des perspectives importantes :
Rang
Pays
Observations Clés
1
Irlande
Le pays qui, par habitant ou par dollar de PIB, contribue le plus au monde. Salué pour sa capacité à maintenir ses devoirs internationaux tout en se relevant d'une grave récession.
2
Finlande
Très proche de l'Irlande, avec des scores globalement élevés.
13
Allemagne
21
États-Unis
66
Mexique
95
Russie
Pays en développement focalisé sur sa construction interne.
107
Chine
Pays en développement focalisé sur sa construction interne.
• Domination Européenne : Le top 10 est majoritairement composé de pays riches d'Europe occidentale (à l'exception de la Nouvelle-Zélande).
• L'Importance de l'Attitude : La présence du Kenya dans le top 30 est cruciale.
Elle prouve que la contribution au monde n'est pas qu'une question d'argent, mais "d'attitude", de "culture" et de volonté politique de se tourner vers l'extérieur.
Les données complètes de l'indice sont accessibles sur le site goodcountry.org
.
La finalité de ce projet n'est pas seulement de classer les pays, mais de changer radicalement le dialogue public et politique.
Anholt exprime sa lassitude face à un vocabulaire centré sur l'égoïsme national : "J'en ai assez d'entendre parler de compétitivité.
J'en ai assez d'entendre parler de prospérité, de richesse, de croissance rapide. J'en ai assez d'entendre parler de pays heureux parce que ça reste quand même égoïste."
Il propose de réinjecter le mot "bon" (au sens de "non-égoïste") dans la conversation.
Ce mot doit devenir un "bâton qui s'abattrait sur nos politiciens".
Les citoyens sont invités à utiliser ce critère pour juger les politiques et les dirigeants en se posant la question :
Question clé : "Est-ce qu'un bon pays ferait ça ?"
L'objectif ultime est de faire évoluer les mentalités, pour que le désir principal des citoyens ne soit plus de vivre dans un pays riche ou compétitif, mais dans un "bon pays".
Un pays dont on peut être fier à l'international, car il est reconnu pour sa contribution positive au monde entier.
The magnitude of the electrical field in the space between the parallel plates is E=σ/ϵ0, where σ denotes the surface charge density on one plate (recall that σ is the charge Q per the surface area A)
This has been proven before in chapter 6 and 7.
Synthèse du MIPEX 2025 : Politiques d'Intégration en France
L'analyse des politiques d'intégration de la France dans le cadre du Migrant Integration Policy Index (MIPEX) 2025 révèle un tableau contrasté.
Avec un score global de 56 sur 100, la France se positionne à mi-chemin, appliquant des politiques qui offrent des opportunités mais aussi des obstacles significatifs à l'intégration.
Cette note, inchangée depuis 2019, masque des évolutions divergentes :
des progrès notables dans le domaine de l'éducation sont contrebalancés par des reculs en matière d'accès aux soins de santé et de résidence permanente.
L'approche française est classée comme "Intégration Temporaire", un modèle qui accorde des droits fondamentaux aux citoyens non-européens mais leur refuse la sécurité à long terme nécessaire pour s'établir durablement et participer pleinement à la vie citoyenne.
Les points forts de la France résident dans son cadre législatif solide en matière de lutte contre les discriminations et dans les récentes améliorations de l'accès à l'enseignement supérieur.
Cependant, ces avancées sont minées par des politiques restrictives concernant la résidence permanente, le regroupement familial et un processus d'accès à la nationalité jugé discrétionnaire et politisé.
La loi "Immigration & Intégration" de janvier 2024 et les décrets d'application subséquents marquent un tournant vers une approche plus sélective et exigeante, renforçant les exigences linguistiques et civiques.
Pour améliorer son modèle, il est recommandé à la France d'adopter une approche plus cohérente, alignant ses politiques sur un objectif d'intégration à long terme et traitant les immigrés comme de futurs citoyens plutôt que comme des résidents temporaires.
Avec un score de 56 sur 100, les politiques d'intégration de la France sont jugées "à mi-chemin" (halfway to promote societal integration).
Ce score place la France dans la catégorie de l'"Intégration Temporaire". Selon la typologie du MIPEX, ce modèle se caractérise par :
• L'octroi de droits fondamentaux et de certaines mesures favorisant l'égalité des chances.
• Le refus de la sécurité à long terme indispensable pour s'installer de manière permanente, investir dans l'intégration et participer pleinement en tant que citoyen.
• La perpétuation d'une perception des immigrés comme étant partiellement égaux, mais restant fondamentalement des étrangers (outsiders).
Cette approche contraste avec celle des pays du "Top Ten" du MIPEX, qui traitent les immigrés comme des égaux, des voisins et des citoyens potentiels, investissant dans l'intégration comme un processus mutuel bénéfique pour l'ensemble de la société.
Le score global de la France est stable depuis 2019, mais cette stabilité cache des changements contradictoires dans différents domaines politiques.
Changements Positifs :
• Accès à l'enseignement supérieur : Des programmes ciblés ont été mis en place pour améliorer l'accès des migrants à l'enseignement supérieur.
• Intégration dans le corps enseignant : Des initiatives soutiennent l'intégration des migrants dans la profession d'enseignant.
• Projets spécifiques :
◦ AIMES+ (depuis 2023) : Vise à améliorer la qualité des cours de français pour les étudiants immigrés.
◦ L'Université en Exil (UXIL) : Offre un parcours académique aux étudiants et chercheurs en exil.
Changements Négatifs :
• Résidence permanente : Les conditions de renouvellement du statut de résident permanent ont été durcies, notamment par la réduction des périodes d'absence autorisées hors du territoire français.
• Accès aux soins de santé (depuis 2020) : Les demandeurs d'asile et les immigrés non-européens font face à des obstacles accrus, avec des conditions supplémentaires et des délais d'attente plus longs pour la couverture santé.
Un changement juridique clé en 2019 a introduit un délai de carence de trois mois et une condition de résidence minimale pour l'éligibilité à la Protection Universelle Maladie (PUMa).
• Loi "Immigration & Intégration" (janvier 2024) : Cette loi, dont le score n'est pas encore intégré au MIPEX, a centralisé et renforcé les exigences en matière de langue, de civisme et d'emploi.
Elle introduit des limites au renouvellement des titres de séjour temporaires et des tests de langue et de valeurs plus stricts pour la résidence et la citoyenneté.
Les décrets et circulaires de mi-2024 et début 2025 ont activé ce cadre, augmentant la pression administrative et les obligations d'intégration.
Domaine Politique
Classification MIPEX
Résumé des Constatations
Mobilité sur le Marché du Travail
Halfway favourable (Moyennement favorable)
Les résidents permanents et les familles ont accès au marché du travail, mais sont exclus de plus de professions réglementées que dans tout autre pays.
Les nouveaux arrivants ont accès aux services généraux d'emploi mais souvent pas à la reconnaissance de leurs diplômes ou à des bourses d'études.
Regroupement Familial
Halfway favourable (Moyennement favorable)
Les exigences (économiques, logement) sont strictes et le processus peut être long et discrétionnaire.
Cependant, une fois réunies, les familles bénéficient de droits socio-économiques égaux et d'un soutien à l'intégration, avec une augmentation des heures de cours de langue (jusqu'à 400h, et 600h pour les personnes analphabètes).
Éducation
Halfway favourable (Moyennement favorable)
La France a renforcé son soutien, notamment via des programmes ciblés depuis 2015 (AIMES+, UXIL).
Tous les élèves, quel que soit leur statut, ont les mêmes droits à l'éducation.
Le point faible reste l'absence de valorisation de la diversité dans l'éducation à la citoyenneté.
Santé
Slightly favourable (Légèrement favorable)
Le système de santé est inclusif, mais il ne répond que faiblement aux besoins spécifiques des patients migrants.
Depuis 2020, les barrières à l'accès se sont renforcées pour les demandeurs d'asile et les immigrés non-UE (conditions plus strictes, délais d'attente allongés).
Participation Politique
Halfway favourable (Moyennement favorable)
Les étrangers sont peu informés et consultés par les autorités.
La France est l'un des rares grands pays de destination sans droit de vote local pour les étrangers.
Une consultation accrue des groupes de réfugiés est notée au niveau national depuis 2018.
Résidence Permanente
Halfway favourable (Moyennement favorable)
L'accès au statut sécurisé de 10 ans est conditionné par des exigences linguistiques, d'intégration et parfois économiques parmi les plus restrictives.
Bien que le statut lui-même soit protecteur, il est très difficile à obtenir et à renouveler (notamment depuis 2024).
Accès à la Nationalité
Slightly favourable (Légèrement favorable)
Le parcours est similaire à d'autres pays occidentaux (5 ans de résidence, double nationalité possible).
Cependant, le processus est de plus en plus politisé, discrétionnaire et décourageant pour certains candidats.
Les exigences strictes (stabilité financière, niveau B1 en langue, entretien d'assimilation subjectif) constituent des barrières importantes.
Antidiscrimination
Slightly favourable (Légèrement favorable)
Il s'agit du plus grand point fort de la France en matière d'intégration.
La législation est solide et l'organe de défense (Défenseur des Droits) est efficace pour informer le public et aider les victimes.
Ces politiques semblent avoir eu un impact positif à long terme sur les mentalités publiques en Europe.
Le modèle d'intégration français est marqué par une incohérence fondamentale :
ses forces reconnues en matière de lutte contre la discrimination et
ses progrès dans l'éducation sont sapés par une approche restrictive et précaire concernant les piliers de l'intégration à long terme que sont la résidence, la famille et la nationalité.
La loi de 2024, les nouvelles instructions préfectorales sur la naturalisation (mai 2025) et une proposition de 2024 remettant en cause le droit du sol témoignent d'un changement de discours vers des politiques d'intégration plus exclusives.
Pour renforcer son modèle, la France devrait :
1. Adopter une Approche Cohérente : Aligner les politiques restrictives de résidence et de regroupement familial sur ses mesures plus inclusives en matière d'éducation et d'antidiscrimination.
2. Sécuriser les Parcours d'Intégration : Réduire le caractère discrétionnaire et les exigences excessives dans les procédures d'accès à la résidence permanente et à la nationalité pour offrir la stabilité nécessaire à une intégration réussie.
3. Traiter les Immigrés comme de Futurs Citoyens : Mettre en œuvre une vision de l'intégration comme un processus à double sens qui renforce la confiance mutuelle et bénéficie à l'ensemble de la société.
Comme le démontrent 130 études scientifiques indépendantes utilisant les données du MIPEX, la manière dont les gouvernements traitent les immigrés est un facteur déterminant qui influence non seulement l'acceptation par le public, mais aussi le sentiment d'appartenance, la participation et même la santé des immigrés dans leur nouveau pays.
eleanor [@zornsllama]. Blue line: daily COVID cases in the USA red line: bad reviews of Yankee Candles on Amazon saying "they don't have any scent" sources: google and https://t.co/oZm6ro0E1S. December 2021. URL: https://twitter.com/zornsllama/status/1473575508784955394 (visited on 2023-12-05).
This tweet is explaining that a candle doesn't have a scent but in all reality that person most likely has covid. Making the review false and misinformative, almost acting as an unintentional case of data poisoning.
Samantha Cole. People Are Spamming Kellogg’s Job Applications in Solidarity with Striking Workers. Vice, December 2021. URL: https://www.vice.com/en/article/v7dvy9/spamming-kelloggs-job-
Kellogg at the time of this articles publication have been trying to hire new workers to replace the previous workers who have gone on strike due for better wages and working conditions. To fight this, people from the antiwork subreddit have been spamming the job portal site to fight back. The union went on strike after the company refused to meet with the union, so Kellogg tried to hire another 1,400 employees. The members of antiwork then repeated sent Kellogg fake applications that were either completely made up people in the cities that Kellogg was hiring from, or just resumes from google images.
Kurt Wagner. This is how Facebook collects data on you even if you don’t have an account. Vox, April 2018. URL: https://www.vox.com/2018/4/20/17254312/facebook-shadow-profiles-data-collection-non-users-mark-zuckerberg (visited on 2023-12-05).
This URL is about Facebook collecting data on people who do not sign up for Facebook. It uses “shadow profile” to achieve that. Shadow profile is when Facebook already has enough data to create a profile even though people don’t use it anymore. It also talked about how Facebook use browsing history and information from users’ friends to collect data from non-users. Facebook uses those datasets for analytics. It is very interesting that there is actually no way to stop Facebook from collecting non-users’ data.
8.9. Bibliography# [h1] Web tracking. October 2023. Page Version ID: 1181294364. URL: https://en.wikipedia.org/w/index.php?title=Web_tracking&oldid=1181294364 (visited on 2023-12-05). [h2] Kurt Wagner. This is how Facebook collects data on you even if you don’t have an account. Vox, April 2018. URL: https://www.vox.com/2018/4/20/17254312/facebook-shadow-profiles-data-collection-non-users-mark-zuckerberg (visited on 2023-12-05). [h3] API. November 2023. Page Version ID: 1187436026. URL: https://en.wikipedia.org/w/index.php?title=API&oldid=1187436026 (visited on 2023-12-05). [h4] Ilya (Marshal) Siamionau. Getting Started: The AT Protocol SDK. 2024. URL: https://atproto.blue/readme.html (visited on 2025-04-03). [h5] Ilya (Marshal) Siamionau. Client - atproto. 2024. URL: https://atproto.blue/atproto_client/client.html (visited on 2025-04-03). [h6] Atproto/examples at main · MarshalX/atproto. 2025. URL: MarshalX/atproto (visited on 2025-04-03). [h7] AT Protocol. 2025. URL: https://atproto.com/ (visited on 2025-04-03). [h8] Everything Everywhere All at Once. December 2023. Page Version ID: 1188074672. URL: https://en.wikipedia.org/w/index.php?title=Everything_Everywhere_All_at_Once&oldid=1188074672 (visited on 2023-12-05). [h9] Jordan Pearson. Your Friends’ Online Connections Can Reveal Your Sexual Orientation. Vice, September 2014. URL: https://www.vice.com/en/article/gvydky/your-friends-online-connections-can-reveal-your-sexual-orientation (visited on 2023-12-05). [h10] Catherine Stinson. The Dark Past of Algorithms That Associate Appearance and Criminality. American Scientist, January 2021. URL: https://www.americanscientist.org/article/the-dark-past-of-algorithms-that-associate-appearance-and-criminality (visited on 2023-12-05). [h11] Greg Miller. Researchers are tracking another pandemic, too—of coronavirus misinformation. Science, March 2020. URL: https://www.science.org/content/article/researchers-are-tracking-another-epidemic-too-misinformation (visited on 2023-12-05). [h12] eleanor [@zornsllama]. Blue line: daily COVID cases in the USA red line: bad reviews of Yankee Candles on Amazon saying "they don't have any scent" sources: google and https://t.co/oZm6ro0E1S. December 2021. URL: https://twitter.com/zornsllama/status/1473575508784955394 (visited on 2023-12-05). [h13] Spurious relationship. November 2023. Page Version ID: 1184161183. URL: https://en.wikipedia.org/w/index.php?title=Spurious_relationship&oldid=1184161183 (visited on 2023-12-05). [h14] Tyler Vigen. Spurious correlations. November 2023. URL: http://tylervigen.com/spurious-correlations (visited on 2023-12-05). [h15] ABC News: 538. 2023. URL: https://abcnews.go.com/538 (visited on 2023-12-05). [h16] FiveThirtyEight. 2023. URL: https://projects.fivethirtyeight.com/p-hacking/ (visited on 2023-12-05). [h17] Christie Aschwanden. Science Isn’t Broken. FiveThirtyEight, August 2015. URL: https://fivethirtyeight.com/features/science-isnt-broken/ (visited on 2023-12-05). [h18] Dan Sabbagh. Trump 2016 campaign 'targeted 3.5m black Americans to deter them from voting'. The Guardian, September 2020. URL: https://www.theguardian.com/us-news/2020/sep/28/trump-2016-campaign-targeted-35m-black-americans-to-deter-them-from-voting (visited on 2023-12-05). [h19] Marie C. Baca. Housing companies used Facebook’s ad system to discriminate against older people, according to new human rights complaints. Washington Post, September 2020. URL: https://www.washingtonpost.com/technology/2019/09/18/housing-companies-used-facebooks-ad-system-discriminate-against-older-people-according-new-human-rights-charges/ (visited on 2023-12-05). [h20] Nicole Nguyen. Here's Who Facebook Thinks You Really Are. September 2016. Section: Tech. URL: https://www.buzzfeednews.com/article/nicolenguyen/facebook-ad-preferences-pretty-accurate-tbh (visited on 2024-01-30). [h21] Lindsey Murray. Here's How to Find Out Everything Facebook Knows About You. May 2017. Section: Life. URL: https://www.goodhousekeeping.com/life/news/a44016/facebook-privacy-ad-settings/ (visited on 2024-01-30). [h22] Rafi Letzter. A teenager on TikTok disrupted thousands of scientific studies with a single video. The Verge, September 2021. URL: https://www.theverge.com/2021/9/24/22688278/tiktok-science-study-survey-prolific (visited on 2023-12-05). [h23] Lauren Leffer. CNET Is Reviewing the Accuracy of All Its AI-Written Articles After Multiple Major Corrections. Gizmodo, January 2023. URL: https://gizmodo.com/cnet-ai-chatgpt-news-robot-1849996151 (visited on 2023-12-05). [h24] Why can't I use Artificial Intelligence tools to generate answers? - Help Center. 2023. URL: https://stackoverflow.com/help/ai-policy (visited on 2023-12-08). [h25] Samantha Cole. People Are Spamming Kellogg’s Job Applications in Solidarity with Striking Workers. Vice, December 2021. URL: https://www.vice.com/en/article/v7dvy9/spamming-kelloggs-job-applications-strike (visited on 2023-12-05). [h26] Antiwork: Unemployment for all, not just the rich! 2023. URL: https://www.reddit.com/r/antiwork/ (visited on 2023-12-05). [h27] Karen Hao. How to poison the data that Big Tech uses to surveil you. MIT Technology Review, March 2021. URL: https://www.technologyreview.com/2021/03/05/1020376/resist-big-tech-surveillance-data/ (visited on 2023-12-05).
I looked at the Vox article by Kurt Wagner, “This is how Facebook collects data on you even if you don’t have an account.” I found it pretty shocking that Facebook can still track people who never even signed up. The article explains that Facebook builds what they call “shadow profiles” using data from other websites and users who do have accounts. It really made me think about how hard it is to stay completely private online — even if you try to avoid social media, your info can still end up being collected. It connects to this chapter’s point about how data gives companies power, because it shows how they can gather information on almost anyone, whether you consented or not.
Web tracking. October 2023. Page Version ID: 1181294364. URL: https://en.wikipedia.org/w/index.php?title=Web_tracking&oldid=1181294364 (visited on 2023-12-05).
By reading this Wikipedia, I understand how web track works and how the data collected in web tracking can be used. From my personal opinion, I think the web tracking is highly related to users’ privacy. It’s important for the tech companies to protect the data they collected.
People in the antiwork subreddit [h26] found the website where Kellogg’s posted their job listing to replace the workers. So those Redditors suggested they spam the site with fake applications, poisoning the job application data, so Kellogg’s wouldn’t be able to figure out which applications were legitimate or not (we could consider this a form of trolling). Then Kellogg’s wouldn’t be able to replace the striking workers, and they would have to agree to better working conditions.
I think that it's fascinating that the term used is poison. Almost implying that it will affect or poison others, like the internet is connected and that we can work together just like in real life.
Thanks so much, I have been struggling with this for a long time!
https://www.tensorflow.org/text/tutorials/text_generation document is failing in the Tensorflow v2.17 which contains Keras3.0. Modified the code to the Keras2.0.
The choice of words and phrases in a question is critical in expressing the meaning and intent of the question to the respondent and ensuring that all respondents interpret the question the same way. Even small wording differences can substantially affect the answers people provide.
This line stood me as this really shows how people can see and interpret language easily even when researcher think that they are being neutral. I remember in INFO 300 that research should be as neutral as possible. I also agree with this because, the small wording in a conversation can make a break a conversation and that also applies here. Overall, this whole reading helped me see that making question needs to consider ethical thoughs in it.
Maybe try changing this line in autogpt/processing/text.py ? def split_text(text: str, max_length: int = 8192) -> Generator[str, None, None]: honestly, I'm still checking to see if that'd be it, but doubtful lol
Andthank God she was there, for I was filled with that icy dreadagain. Everything I did seemed awkward to me, and every-thing I said sounded freighted with hidden meaning. I wastrying to remember everything I'd heard about dope addictionand I couldn't help watching Sonny for signs. I wasn't doing itout of malice. I was trying to find out something about mybrother. I was dying to hear him tell me he was safe.
From this passage we can see the narrator keeps looking after his brother for fear of him being trapped by drugs again ;the theme of the obligation toward brotherly love.
We might want to discuss something privately, avoiding embarrassment that might happen if it were shared publicly
I agree that this is a good reason that we have to keep information private. Without privacy, every conversation will be public, and nobody wants to show all of their messages to the people around the world. Therefore, privacy gives users reassuring environment to discuss.
Version 5 of this preprint has been peer-reviewed and recommended by Peer Community in Mathematical and Computational Biology.<br /> See the peer reviews and the recommendation.
epen staff understanding. It’s crucial for educators to keep in mind the many factors, some of them invisible, that play a role in students’ class-room actions. Many nonminority or middle-class teachers cannot under-stand why children from poor backgrounds act the way they do at school. Teachers don’t need to come from their students’ cultures to be able to teach them, but empathy and cultural knowledge are essential. Therefore, an introduction to how students are affected by poverty is highly useful.Consider summarizing information from this chapter or other sources and sharing it with staff. Hold discuss
I find this passage meaningful because it reminds teachers that students’ behavior often reflects hidden struggles rather than lack of effort. I agree that empathy and cultural understanding are key for educators to truly connect with and support students from low-income backgrounds. My question is how schools can ensure that this kind of professional learning becomes a lasting part of teacher training instead of just a one-time workshop.
mon issues in low-income families include depression, chemical dependence, and hectic work schedules—all factors that interfere with the healthy attachments that foster children’s self-esteem, sense of mastery of their environment, and optimistic attitudes. Instead, poor children often feel isolated and unloved, feelings that kick off a downward spiral of unhappy life events, including poor academic performance, behavioral problems, dropping out of school, and drug abuse. These events tend to rule out col-lege as an option and perpetuate the cycle of poverty. Figure 1.1 shows how 1.1 Adverse Childhood Experiences ModelSource: Adapted from “Relationship of Childhood Abuse and Household Dysfunction to Many of the Leading Causes of Death in Adults: The Adverse Childhood Experiences (ACE) Study,” by V. J. Felitti, R. F. Anda, D. Nordenberg, D. F. Williamson, A. M. Spitz, V. Edwards, et al., 1998, American Journal of Preventive Medicine, 14(4), pp. 245–258.Early DeathDisease, Disability, and Social ProblemsAdoption of Health Risk BehaviorsSocial, Emotional, and Cognitive ImpairmentAdverse Childhood ExperiencesDeathConceptionJensen.indb 5Jensen.indb 510/26/09 1:39 PM10/26/09 1:39 PM EBSCOhost - printed on 10/29/2021 10:58 PM via EL CAMINO COLLEGE. All use subject to https://www.ebsco.com/terms-of-use
I find this passage powerful because it reveals how emotional struggles and unstable home environments can deeply affect children’s confidence and future. I agree that without strong attachments and support, many children may lose hope and fall into a cycle that keeps them from education and opportunity. My question is how schools or communities can step in early to rebuild that sense of belonging and help break this pattern before it becomes permanent.
lthough childhood is generally considered to be a time of joyful, care-free exploration, children living in poverty tend to spend less time fi nd-ing out about the world around them and more time struggling to survive within it. Poor children have fewer and less-supportive networks than their more affl uent counterparts do;
I find this passage sad but eye-opening because it shows how poverty can take away a child’s chance to explore and learn freely. I agree that limited resources and weaker social networks make it harder for poor children to develop both emotionally and cognitively. My question is how schools and communities can create more equal learning environments so that every child has the chance to grow with curiosity instead of just survival.
Relative poverty refers to the economic status of a family whose income is insuffi cient to meet its society’s average standard of living.• Urban poverty occurs in metropolitan areas with populations of at least 50,000 people. The urban poor deal with a complex aggregate of chronic and acute stressors (including crowding, violence, and noise) and are dependent on often-inadequate large-city services. • Rural poverty occurs in nonmetropolitan areas with populations below 50,000. In rural areas, there are more sin
I find it interesting how poverty can look so different depending on where people live, and that urban and rural families face completely different challenges. I agree that city life brings stress from noise and crowding, while rural areas suffer from isolation and fewer services, yet both situations limit opportunities for children. My question is how governments and schools can design programs that truly fit the needs of these very different communities instead of offering one single solution.
eel if your son or daughter were a student in Mr. Hawkins’s class? Only two short generations ago, policymakers, school lead-ers, and teachers commonly thought of children raised in poverty with sym-pathy but without an understanding of how profoundly their chances for success were diminished by their situation. Today, we have a broad research base that clearly outlines the ramifi cations of living in poverty as well as evi-dence of schools that do succeed with economically disadvantaged students. We can safely say that we have no excuse to let any child fail. Poverty calls for key information and smarter strategie
I find this passage powerful because it shows how much progress education has made in understanding the effects of poverty, and it reminds me that teachers can truly change the path of disadvantaged students. I agree that knowing the challenges of poverty should lead to better strategies instead of lower expectations, since every child deserves a fair chance to succeed. My question is how schools can prepare teachers to recognize and respond to poverty in a way that empowers students rather than making them feel pitied.
simultaneously look at something in the real world and a digital overlay at the same time.
nice use case, continue using laptop normally, and then when u need something more private, use the glasses
Mia Jankowicz. A TikToker said he wrote code to flood Kellogg with bogus job applications after the company announced it would permanently replace striking workers. Business Insider, December 2021. URL: https://www.businessinsider.com/tiktoker-wrote-code-spam-kellogg-strike-busting-job-ad-site-2021-12 (visited on 2023-12-05).
Is this not a beneficial form of trolling? At the end of the day, trolling is a disruption of established order we are expected to follow. While this order is generally important for us to follow, it is created by those above us to control us. And when we use the internet, an invention of those above us, to disrupt the order that benefits them, I see that as a positive action.
We th
TEXT: "We the undersigned" is metaphoric in the sense that we, the people have the power to make political change. "Agree to wear our hearts on our sleeves means to be open about our feelings, like showing kindness, its telling us to be less cold and or distant. This poster takes "we the undersigned" to remind people to stay kind in a world of cold and distant individuals, in which empathy, kindness are a power, we the citizens have.
COMPOSITION: The fist in the background is a symbolic, meaning strength, power, and so forth. It is commonly used in social and political movements. Then underneath the bold semi canalized text is a bunch of signatures meaning agreement and solidarity, in which to lessen the world of cold and distance within individuals, we need to come together. This is further solidified by "join in solidarity." In addition this page many official stamps and symbols, almost giving it an official feel, like this is an agreement policy, and the signs below is all the people who agree with this.
One of the main goals of social media sites is to increase the time users are spending on their social media sites. The more time users spend, the more money the site can get from ads, and also the more power and influence those social media sites have over those users. So social media sites use the data they collect to try and figure out what keeps people using their site, and what can they do to convince those users they need to open it again later.
My first though when I saw this is that they've been doing well on keeping people using their site. Personally, I am really affected by this because it works so well and I spend so much time on scrolling on my phone. Although this help people to see more interesting content but it really makes people addicted to the internet.
Social Media platforms use the data they collect on users and infer about users to increase their power and increase their profits. One of the main goals of social media sites is to increase the time users are spending on their social media sites. The more time users spend, the more money the site can get from ads, and also the more power and influence those social media sites have over those users. So social media sites use the data they collect to try and figure out what keeps people using their site, and what can they do to convince those users they need to open it again later. Social media sites then make their money by selling targeted advertising, meaning selling ads to specific groups of people with specific interests. So, for example, if you are selling spider stuffed animal toys, most people might not be interested, but if you could find the people who want those toys and only show your ads to them, your advertising campaign might be successful, and those users might be happy to find out about your stuffed animal toys. But targeting advertising can be used in less ethical ways, such as targeting gambling ads at children, or at users who are addicted to gambling, or the 2016 Trump campaign ‘target[ing] 3.5m black Americans to deter them from voting’ [h18].
Honestly, it’s kind of wild how social media uses our data to keep us hooked. I get how targeted ads can be helpful sometimes, like showing you stuff you might actually want, but it also feels manipulative. The part that stood out to me most is how they use data to figure out what keeps people on the app longer—it’s like they’re studying us just to make sure we don’t stop scrolling. I’ve definitely noticed that when I like one type of video, suddenly my feed is full of that topic, and it’s super easy to waste time without realizing it. It makes me wonder how much control we really have over what we see online.
izen is a letterp
Text: The phrase "I'm a citizen of a borderless country" seems to say that there is a rejection of nationalism and national boundaries. Then it says "whose flag is a worn tablecloth. This metaphor seems normalize the flag, as more so something humble and seen everyday. The line "whose constitution is a broken loaf of bread" seems to hints at the vulnerability, and fragilness of a country. This poster's main message is saying that true citizenships is flawed, and isn't just about politics, it also involves humanity, and togetherness.
COLOR: These poster consist of mainly white with a combination of red and blue at the bottom of the poster. The use of white means purity, innocence, and so forth. While, red means more so intensity, and blue means calmness and stability. The minimalistic of this poster makes the message stand. The white background makes it feel there is more innocence within a country. While the other colors seem to hint at less noticeable feelings in this country concept, calmness and passion.
“Bad faith” here means pretending to hold views or feelings, while not actually holding them (this may be intentional, or it may be through self-deception).
As much as I enjoy the concept of trolling and feel that it's one of the most unique parts of the internet, bad faith arguing has gotten so out of control and soiled so much discourse that takes place online. The idea that now people will engage in discussions or arguments while positing opinions and ideas they don't really stand for completely derails the concept of debate in the first place, and so while I enjoy a bit of trolling here and there, bad faith I believe is just unhealthy.
You can try social media sites as well. Twitter’s ad profile is located here
I did this with my Twitter profile and the results were interesting. The Twitter personalized ads profile area is organized with a list of everything that Twitter thinks you're interested in. For me, I found that my list was so massive and overly generous with what it thinks I like. It was filled with a non-insignificant amount of things that I have never heard of that Twitter thought interested me. I'm not sure if this is intentional or not, because I feel having a bunch of stuff I'm not interested in would make it harder to advertise stuff to me.
Generative AI creation can be both infringing as well as non-infringing, copyright within its periphery has means to deal with the infringing content, copyright should not be used as a tool to end the generative AI creation.69 Copyright law should be used as a tool to correct the infringing aspects, if any in copyright law from time to time
Managing copyright law for AI music generation has to be done very carefully.
different standards for machine creation. It would also reset the copyright infringement standards to a difficult level that would deter the objective of the Law where one would not be able to create without infringing the Law. The law would become counterproductive and supress creativity instead of encouraging it.
While copyright laws are important, they can't become so extreme that they discourage creation.
This paper is rather an attempt to say that the infringement analysis should be done on the output of the generative AI and not on its training.
Output should be regulated, not training data.
It has explained the major concerns around the concept of training what Prof. Lemley calls as ‘fair learning’. And further has raised questions regarding the infringement analysis of AI-generated music. It has also shown the possible alternate to the existing test of copyright infringement, and the problems of utilising AI tools to address the issues caused by Generative AI.
Currently using copyrighted works for training data is fair use as it is used for learning purposes.
SUNO AI claims to be the first Author of music when generated using its basic version and if the song is generated through a premium version of the same platform, the user becomes the owner of the song and enjoys a licence to commercially license the same
The user became the owner of a song that was not theirs.
Even musicians have begun to adopt the usage of SUNO AI, which shows the acceptance of this from the creative community.
You can make money creating music with AI.
having a copyright protection over a work does not guarantee any monetary returns in it, and the vice versa is equally true. Copyright protection is an incentive to create music, it is not a pre-requisite for creating music.
Copyright helps you but does not make you immune to infringement.
more dissimilarities than similarities.
This is the main principle copyright is based on.
Though, it may have similarities on the surface, deep within they are different, and cannot be considered as same just because they belong to the same tune.61 It is not possible to grant protection to the tune itself. If given, it runs the risk of monopolising a commonly held substance that is free for all to use.
There are plenty of examples of indirect, unintentional plagiarism in music that is inevitable.
Within a song there are always ‘protectable’ and ‘unprotectable elements’, and as mentioned in the previous paragraph, melody is the protectable element in copyright law; by replacing the existing test of substantial similarity from lay observers, we might run the risk of granting protection to unprotectable elements and could turn the copyright infringement jurisprudence upside down.
Under current copyright laws, most AI music plagiarism instances are under protectable elements.
Unless the Generative AI platform generates songs on a particular style/particular voice, it may be difficult to prove before the court that the platform is trained upon the specific copyrighted material. The current form of copyright Act does not look at copyright infringement through the input, it looks at it through the lens of output.
There is currently no clause of the copyright act that can prevent infringement of similar creations.
This note-by-note fragmentation has not been the objective of law, if the test were to be replaced with finer tests, one could never create music without violating copyright law, applicable both for humans and machines as the percentage of similarity between two songs could be similar that does not necessarily mean that the songs are substantially similar/same.
Notes are too small a detail to copyright.
The platform does not thieve on any individual's voice or does not use any individual's voice or style, for instance, even if given a prompt to provide music like Mr. Frank Sinatra, it does not provide any output, the idea behind this is probably to exempt themselves from any violation of personality rights/moral rights.
This means that the copyright safeguard does work.
The AI-generated song does not have a separate composition alone. It is created as a recording itself, unlike the traditional understanding of creation, where the composition composed and then it is recorded.
The two pieces of copyright from before, composition and recording, are only one step in AI music creation; it is composed as a recording.
A decade ago, sampling of music raised a similar copyright concern from the right holders. Sampling is a process by which composers rely on portions from a previous song to create a subsequent work, courts in the United States held, sampling of music cannot be done without taking license from the rights holders.
Sampling, regardless of how short, still requires permission from the artist.
The melody has multiple musical elements that may be working together, the individual elements do not enjoy separate protection under the realm of copyright law. The unprotected element and the protected elements are so intertwined that the protected elements under the musical creation cannot be heard without the unprotected elements.
There are so many ways to arrange individual elements that songs can be rearranged and become unrecognizable.
There is a problem when someone begins to understand the concept of ‘musical copyright infringement’, there is no single accepted definition of a ‘song/musical work’. The inherent nature of ‘music’ makes it difficult to identify the infringing element in the work.
This is true, where is the line drawn, a track of a song, a chord progression, a small string of notes, or a very similar layout or style, there isn't one answer.
‘Melody’ is the only part of the music that could be notated on a piece of paper, and rest can only be recorded. A song enjoys two separate sets of copyrighted protection, (i) the composition and (ii) recording.
Composition and recording are considered two separate pieces of copyright, as a song can be significantly altered through different recording techniques.
One particularly striking example of an attempt to infer information from seemingly unconnected data was someone noticing that the number of people sick with COVID-19 correlated with how many people were leaving bad reviews of Yankee Candles saying “they don’t have any scent”
This paragraph provides an excellent example of data mining, the researchers can use data they collected from the seemingly irrelevant incidents to find what exactly they need.