Review of <i>Dear Science and Other Stories</i> by Katherine McKittrick (Duke University Press)
Bibliographic record
Abstract
With 'Dear Science and Other Stories,' Katherine McKittrick does the work of liberation and enacts new ways of being. Building on her previous studies, this collection engages in a story-sharing, collaborative praxis that emerges from a "black sense of place." McKittrick's Black and anti-colonial methodologies are "rebellious," "relational, intertextual, and interdisciplinary"—thereby "breaching" the "recursive," "self-replicating" logics of "our present order of knowledge" (44, 2, 23, 163). 'Dear Science' invents, reinvents, and reimagines "being human as praxis" through an aesthetic practice of deciphering theoretical texts, photographs, sounds, dance, and song (159). Illustrating her commitment to Black intellectual life, McKittrick writes, listens, and feels in communion with other creatives. In so doing, McKittrick skillfully bursts open the gatekeeping conventions that limit thought, and challenges readers to question what they think they know.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".