Bibliographic record
Abstract
This project examined the historic-racial schema articulated by involuntarily celibate male members of the online forum incels.is. Based in a content analysis of images and comments from incels.is, it drew on a broad framework informed by double-consciousness, historic-racial and corporeal schemas, hegemonic and hybrid masculinities, and realistic and symbolic threat. This research documented what assumptions shape said schemas, how incels operationalized racial status and status threat, and how racialized and non-racialized incels incorporated those ideas into their corporeal schemas. It found that processes of racialization on the forum were articulated in a manner consistent with the warped ‘handing back’ of racialized identities described by Fanon and Du Bois. Racialization was akin to a process of objectification and racialized incels interpellated limiting core self-evaluations, while non-racialized incels drew on hybridized masculinities to distance themselves from privilege yet sought to entrench it. Author’s Note: Content warning for discussions of sexual assault and violence against women, dehumanizing language directed against racialized minorities.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".