Challenging Institutional Racism in International Relations and Our Profession: Reflections, Experiences, and Strategies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Attempts to create a more inclusive discipline and profession have been commended by many and derided by some. While these attempts have pushed for change, particularly with regards to more equal representation of gender and race among faculty, policies aimed at creating a more inclusive environment are often tokenistic, administrative and bureaucratic, and fail to address structural and institutional practices and norms. Moreover, the administrative and bureaucratic policies put into place are generally targeted at a single categorical group, failing to take into account the manner in which identities are intersecting and overlapping. Equality, Diversity and Inclusion often gets driven by Human Resources and Marketing rather than owned by the wider university. This forum draws from a variety of contributions that focus on describing the lived realities of institutional racism, its intersections with other forms of discrimination, and strategies for change. In putting together this forum, we do not aim to create a checklist of practical steps. Instead, we hope to signpost and make visible the successes and failures of previous challenges and future possibilities that must be taken by both faculty and administrations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it