“Don't Work for Soyciety:” Involuntary Celibacy and Unemployment
Bibliographic record
Abstract
ABSTRACT Surveys of involuntary celibates (“incels”) suggest that they tend to be not in education, employment or training (NEET) at disproportionately high rates. However, it remains unclear whether and how being NEET is connected to incels' ideology and life circumstances. To investigate this, we conducted a qualitative thematic analysis of over a thousand comments posted on the main incel forum, incels.is. We found that many users promoted unemployment and social disengagement as a form of retaliation against a society they feel has harmed them. These users often encouraged other incels to embrace a life of isolation and used employment status as an assessment of commitment to the incel identity. Users also reported experiences of discrimination, bullying, and feeling incompetent at workplaces and educational institutions. We conclude that, for incels, being unemployed can be both an ideological stance and a consequence of their experienced or perceived marginalization.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".