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Record W4309244684 · doi:10.1007/s11920-022-01382-9

Involuntary Celibacy: A Review of Incel Ideology and Experiences with Dating, Rejection, and Associated Mental Health and Emotional Sequelae

2022· review· en· W4309244684 on OpenAlexaff
Brandon Sparks, Alexandra M. Zidenberg, Mark E. Olver

Bibliographic record

VenueCurrent Psychiatry Reports · 2022
Typereview
Languageen
FieldSocial Sciences
TopicGender, Feminism, and Media
Canadian institutionsUniversity of SaskatchewanThe King's University
Fundersnot available
KeywordsLonelinessPsychologyMental healthRuminationIdeologyAnxietyIdentity (music)Social psychologyClinical psychologyPsychiatryPsychotherapistDevelopmental psychologyPolitical scienceCognition

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Incels (involuntary celibates) have recently garnered media attention for seemingly random attacks of violence. Much attention has centered around the misogynistic and violent discourse that has taken place in online incel forums as well as manifestos written by incels who have perpetrated deadly attacks. Such work overlooks the experiences and issues faced by incels themselves, the majority of which have not engaged in any violent behavior. RECENT FINDINGS: A small number of studies have recruited incels. Results from these studies highlight the nuanced nature of the incel identity. It is also apparent that incels suffer from high levels of romantic rejection and a greater degree of depressive and anxious symptoms, insecure attachment, fear of being single, and loneliness. Incels report significant issues pertaining to their mental, social, and relational well-being and may seek support from forums that often feature misogynistic and violent content.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.004
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.067
GPT teacher head0.390
Teacher spread0.323 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations87
Published2022
Admission routes1
Has abstractyes

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