“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 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 | 0.001 |
| Science and technology studies | 0.001 | 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".