Speaking the unspeakable; or providing the evidence without being censored
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
This article is about the difficulties inherent in using the racist tropes resulting from the transatlantic slave trade to address the chronic persistence of systemic racism. The problem with revealing horrific material – such as the fugitive slave ads I cite from early nineteenth-century Barbados newspapers – is that they raise the risk of causing offence. Yet the point of speaking the unspeakable is to move towards telling truths revealing both the brutality of enslavers and the ingenuity and courage of enslaved individuals who resisted. By focusing on the heroism of people in the fugitive slave ads I shift attention away from the White legislators typically credited with abolition and towards people who consistently resisted enslavement. My account of navigating the treacherous territory of speaking the unspeakable resolves as a cautionary tale about making sure that unspeakable, long concealed material is buffered with trigger warnings and careful explanations as to why it is being revealed.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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