If we really centered marginalized communities, if were accountable to thesecommunities, if we asked ourselves “Who is doing data science, How we aredoing data science, and Why we are doing data science,” and if we are cen-tered on human rights and the human experience, then, would we even needto invoke ethics as a framework for building our future?

Data scienceshould not be content to merely avoid sexism, ableism and racism. Seekingjustice for data science means actively and materially working against thepower structures that support these ”isms.

o we have a responsibility to send lead-ers into the future that can imagine the consequences of their technologicaladvancements and design against it if necessary

I’m thinking about the need for mathematicians inmathematics departments getting involved in developing data science pro-grams to step back and learn from the data science educators who have beendoing the work and thinking about establishing respectful relationships withcommunities.

One pathway is by empowering those in our communities to become datascientists, because of the deep understanding brought and because of thecommitment to accountability.

defining equity as a gapless end state, we sought to contemplatehow we are constructing equity in more materialized senses

“gap-gazing

another intersectiontakes into consideration our different ways of knowing, many of which arerooted in critical and indigenous methodologies, such as storytelling

thismoment presents space for the field to collaboratively explore, critique, andexpand the collective understanding of the cultural, historical, and sociopolit-ical dimensions of equity in the development of data science and data literacypedagogies, and in computational analyses more broadly

slow down

if it is held that the statewide assessment fails to provide important, accurate, or relevant information about the examinee, and/or if the clas-sification mechanism for racial and ethnic groups is unac-ceptably crude or inconsistent, then performance differences between groups provide no useful information, irrespective of statistical significance.

For example, if a researcher wants to compare students’ performance on a statewide assessment along racial and ethnic lines, they are making implicit ontological assumptions about the meaningfulness of the statewide assessment and the classification mechanism for racial and ethnic groups.

The goal is to read the mathematical machinery through a critical lens

from a CQL perspec-tive, is to develop an awareness of what the number does, what it represents, what it does not tell you, and why these pieces of information are important and, accordingly, to identify useful information to supplement the mean

In fact, the core quantitative content of most methods courses need not change

QuantCrit is explicitly an extension of CRT, wherefrom it draws its guiding tenets. CritQuant is devel-oped out of conflict theory and is open to critical theories other than CRT (Boveda et al., 2023).

QuantCrit scholars are explicit about QuantCrit scholar-ship being traceable to Du Bois (1899) and that the frame-work’s tenets are an extension of the well-established CRT tenets into quantitative research

self-reflexive researcher who is critically reflective on the existence and perpetuation of social inequality and who uses quantitative inquiry to illuminate and challenge these inequalities with the aim of social transformation.

These contexts provide an eye-opening backdrop for the contem-porary push to bring criticality into quantitative methods research and education

Pearson,

statistical application in the social sciences began with the eugenics movement

critical quantitative literacy, or CQL, as the critically informed understanding of the scope of quantitative method-ology, including, but not limited to, statistical research

learners of quantitative methodology must be made aware of its historical and modern misuses

P-values

impacts of gender or race gaps but the impacts of sexism and racism.

The lack of data from minoritized students has led many research projects to find that racism’s impacts are not statistically significant and conclude that equity was achieved.

Gaps in student performance result from systems-wide policies and approaches that implicitly and explicitly disadvantage broad groups of students, particularly those that do not identify as white men

researchers attempting to collect information from a diverse set of participants are often blocked by a lack of financial resources and time (Hancock, 2007).

researchers should account for the current limitations that exist in how we assess students’ prior academic preparation.

We further caution against excellence-based approaches that solely center grades or degree attainment.

Focusing solely on gaps is harmful, because it centers students’ identities as the reasons behind their academic failures.

However, each institution, department, and classroom has its own set of historical origins and structural factors that have shaped the present-day experiences for each identity group.

Gutiérrez (2013) argues that focusing on individual groups is not enough, rather that equitable practices within STEM contexts must con-tend with the ways that identity and power manifest in our courses and institutions.

researchers studying achievement gaps in higher education without adequate explanation of structural barriers (Ladson-Billings, 2006; Gutiérrez, 2008)

researchers often implicitly regard themselves as objective observer

These questions can assist researchers in adjusting their methodological approaches

integrate the voices of racially marginalized and minoritized individuals through qualitative and mixed-methods approaches to account for limitations in quantitative interpretations;

we argue that the necessity of integrating critical approaches is directly linked to the need for revision in STEM education.

We argue that engaging in critical research is an effort to re-center the students, to create safer and healthier environ-ments for them to pursue their passions

Critical theories explore how his-torical events and society have shaped present-day experiences and understandings of how the world functions

This rationale works when observing scientific and mathematical phenomena like gravity or volcanic eruptions but breaks down when study-ing human experiences.

we aim to engender reflection and conversation with researchers and practitioners who do STEM equity research so that we all can use quantitative data more responsibly and accurately

Quantitative researchers frequently use students’ test results at an earlier stage of their education as a way to group people of similar ‘ability’ (a maneuver that they claim compares ‘like-with-like’)but this erases racism and blames the students

By applying a statistical model (whichassumesthat poverty, income, maternal education and other ‘family’ characteristics are entirely unrelated to race/racism) the statistician has turned under-representation (minority disadvantage) into over-representation (White disadvantage)

numbers are neither objective nor color-blind.

algorithm

value-free and politically neutral.

data cannot ‘speak for itself

Categories are not natural: for raceread racism-QuantCrit interrogates the nature and consequences of the categories that are used within quantitative research.

Numbers are not neutra

how the everyday use of numbers (especially in news media) can give a false impression of reality.

Behavioral Functioning

family’s socioeconomic resources

sample from 35 states indicate that disparities in advanced mathematics achievement grow between students who are White or Asian and those who are Black or Hispanic across the upper elementary grades

patents

Advanced STEM achievement (e.g., performing above the 90th percentile) by elementary school predicts scientific innovation in adulthood as indicated by being listed as an inventor on a technology patent application

White or Asian students are more likely to complete STEM college degrees

may need to begin by elementary schoo

, working at a federal agency in which sexism and racism openly prevailed.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }.d-519c888e-dece-463b-8a7b-a76c8439062b, .lh-519c888e-dece-463b-8a7b-a76c8439062b { background-color: var(--pubpub-active-discussion-highlight-color, rgba(45, 46, 47, 0.5)) }dot2?Login to discussCancel, who demonstrated that the ideological mission of the United States—as a land based on the ideals of liberty, equality, and opportunity for all—was far from accomplished.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Rachel Shearer