Bibliographic record
Abstract
In this essay, Eve Tuck and Sefanit Habtom consider three contemporary conversations in the field of urban education: Urban education takes place on Indigenous land; diversity is not it, and social movements do more than we can know at a given time. Tuck imagines these may have been conversations that her mentor, Jean Anyon, would be writing, mentoring, or thinking about. Drawing from Anyon and Tuck’s conversations from nearly 20 years ago, the coauthors of this essay are connected within another mentoring relationship. This time, Tuck is the professor and Habtom is a doctoral student. Tuck and Habtom continue the tradition of unfinished conversations that might extend beyond the time frames of a lived life, of a mentoring relationship, and historical moment.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.005 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.013 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".