This is such a powerful project. I really love that it focuses on images-- they're such a rich medium and can often tell us more than articles or other written statements. I think that the exclusionary and racist histories of PWIs have been so clearly swept under the rug without acknowledgement or an attempt to correct. The ramifications of these histories-- and their subsequent erasure-- had and continue to have pernicious effects on students, especially students of color. This is such a valuable and informative project, I look forward to exploring it further. Great job!

I am such a huge fan of this project-- I think it provides an excellent example of how to use digital humanities to hold our institutions accountable. I especially love how Voyant was utilized to examine the language in the climate action plans, I think comparing the frequency of specific words to understand the different approaches to climate action is genius idea. I also really love the interactive timelines! Nice job!

I like this observation about the difference between dynamic vs more static or "tame" maps. It reminds me of the Data Feminism chapter that (I believe) we read for this week, and the notion that sometimes breaking the rules of data visualization, namely creating messy or overwhelming visualizations, can be an effective form of commentary. Obviously this depends on the outlet, and the NYT is primarily focused on providing accessible information rather than an accompanying conclusion. Still, I found it a bit unnerving to see the egregious income inequality in our country represented so "tamely" and without comment.

I think this is a really key observation, both with regard to The Great Gatsby itself, and our expectations for what qualifies as great literature. This point struck me because I've learned that The Great Gatsby was not considered a great piece of literature when it was initially published. It only became popular when it was mass-published as a pocket edition for soldiers in WW2, which led to a re-examination of the novel and its current ubiquity in high school classrooms today. I think this is interesting because you observe that the language isn't as sophisticated or varied as one might expect from a great work of literature, and I wonder if that contributed to its initial lukewarm reception in the literary community.

I think this is a super key consideration, and I think we all have to acknowledge the possibility that our findings for this project are only a part of the story, and may not be representative of the entire campus community. I'm really looking forward to seeing the final project and learning about your interpretation of the results.

The timeline tools are so cool! Both informative and visually appealing-- I like how the headers change and pop up as you scroll through the timeline. Very excited to see the final project and your interpretations of the different colleges' Climate Action Plans!

I like how this group highlights the institutional implementation (or lack thereof) of student activism-- it's such an important component of this discussion and is still super relevant. Earlier in the course, I looked at several objects relating to student activism, and I was really curious about the institutional response/implementation of the demands, so I'm excited to see what this group finds!

I think this is a fantastic-- and incredibly useful-- idea!! Creating a database of college climate change records holds our institutions accountable and facilitates the spread of ideas and strategies across campuses.

I think that the way the Narratives map utilizes occlusion to demonstrate the inherently problematic-- and dehumanizing-- nature of gentrification and using data visualization to depict it. This reminds me of other ethical discussions we've had, about how interpreting certain sources/issues as data can be problematic because it erases personal stories and lived experiences. I really like the idea of making the data visualization purposefully messy and overwhelming. However, I think it's also important to include more understandable visualizations as well, so that people can also understand the problem and be motivated to fix it-- a solution requires both emotion and competence, so we should strive to make our data visualizations easy to understand, but also emotionally impactful.

This is an excellent example of how the digitization of a humanities text can not only reproduce, but actually enhance the value of the original text. I also love how this broadens the accessibility of these letters, and as a result, the mind and life of Van Gogh. Previously, one would have had to be an expert to fully appreciate the value of these letters, but now anyone with access to this source also has access to the context required to fully appreciate the letters.

Wow, what a cool project! I really like Laila's reflection here and application of what we read in chapter 6 of Data Feminism this week. It also reminded me of the section about situated knowledge, which is a vital consideration in these projects, but can also be difficult to fully identify in practice. I also like Laila's point about how a data-driven approach can lead us to lose track of individual stories, which is especially problematic when working with emotional topics.

I think the underlying motives for research/data projects are such a vital, but often ignored, factor of data justice. I really like the framing here how Big Dick Data projects exploit very real data about harm against women in order to further their own objectives. And because the default is so inextricably bound with cis-masculinity and patriarchy, nobody bats an eye, unless a huge obvious error is made, such as was the case with FiveThirtyEight.

I really like how you extrapolate from the observation about the missing metadata and its potential insight into the homosexual community at Swarthmore from that time. These are small details that often go unobserved, but it's fascinating to consider what a small amount of information, such as the number of contributors, could tell us about a community.

I think this is a really fascinating point-- both the observation that power imbalances can be perpetuated through recordkeeping, and that digital platforms enable us to resist further perpetuating them. The example here of utilizing the data from the "White Australia" archives demonstrates how historically oppressed groups can reclaim their heritage and history through data that was originally collected for morally reprehensible purposes.

I really like how you connect privilege hazard here. I'm fascinated by the notion of creating an "Emotional Landscape" and how curation enables creators to provide digital justice to past groups and individuals at an emotional/personal level. I also like your point about the juxtaposition of the maps from opposing vantage points and how you connect it to critically examining our own areas of ignorance.

These manifestations of racism in the digital realms are arguably more subtle, and thus more insidious, than more concrete examples, such as redlining policies or jim crow laws. I think this is mainly because of the over-arching belief that technology and data are neutral-- that because they are not human they are incapable of having a bias or even a perspective. This leads to people completely overlooking the gross biases in our data & the policies it informs.

This is my first time encountering the term minoritized instead of minority groups, and I like it a lot better. From a grammatical perspective, I like that it places the action external to the group, so that the group is receiving the devaluation rather than being identified as minority. It's also more accurate, and inclusive, as it asserts that a group doesn't have to be in the minority in order to be oppressed, thus allowing for a more nuanced understanding of oppression. Further, I've always had a gut sense that minority was a bit pejorative/reductive.

So many different fields grapple with this issue-- how to be interdisciplinary without completely dissolving the lines of distinction. This article focuses quite a lot on categorization/labels, and while I can see the value in that, I also think that we tend to get caught up in these pretty arbitrary definitions. That's why I like a really broad definition of humanities, although I recognize that in academic contexts it needs to be more specific/limited.