Involving Humans, or Doing Good Work With Good People: Insights for Qualitative Research in Black Studies Post-2020
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
." We examine the unprecedented post-2020 climate of invitation and recognition of Black scholars, Black research, "Black excellence," and Black Studies in the Canadian academy and inquire into its implications for research methodologies. We identify the current Canadian academic climate, like those that Wynter examines in her work, as emerging in the aftermath of Black death, anti-Black terror, and race rebellion. We argue that despite the ostensible epiphanies that this moment might be taken to represent, the anti-Black ordering of bodies and knowledge that Wynter outlines might well persist in the Canadian academy embedded in methodologies that produce Black people as non-human. We take seriously the possibility that the new discourses of recognition, invitation, excellence, and incorporation might be the new strategies by which BlackLife is cast beyond the realm of the Human in Canadian universities. As Wynter proffered for Black Studies, we argue that Black research cannot leave the university or its methods intact as it enters the university. We reflect on ways forward for Black researchers that insist on Black humanity in a university context that routinely denies it.
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 | 0.036 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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