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Record W4391215194 · doi:10.1097/jfn.0000000000000472

Making Sense of Schizoposting

2024· article· en· W4391215194 on OpenAlexaff
Jim A. Johansson, Dave Holmes

Bibliographic record

VenueJournal of Forensic Nursing · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicTerrorism, Counterterrorism, and Political Violence
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsRadicalizationScholarshipMental healthPopulationPsychological interventionPsychologyMental health nursingPhenomenonEpistemologySocial psychologySociologyPsychotherapistPolitical sciencePsychiatryTerrorism

Abstract

fetched live from OpenAlex

ABSTRACT: Online radicalization has gained considerable attention in the media and in academia. Much attention has shifted to so-called "homegrown terrorists." Mental health concerns of those who display signs of online radicalization are identified as a potential contributing factor to this process. Although it seems both tempting to attribute mental health concerns, attempts to "make sense" of schizoposting (a bizarre and often violent form of online engagement) via conventional "clinical" analysis prove insufficient. This article offers a critical analysis of an extremely disturbing (online) phenomenon through the radical poststructuralist scholarship of late French philosophers, Deleuze and Guattari. Given that schizoposting and those individuals who engage in this behavior have yet to receive any attention in the nursing and health-related literature, it is critical that future research aims to better understand this population, such that appropriate interventions may be proposed.

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)0.003
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.010
Scholarly communication0.0030.003
Open science0.0000.005
Research integrity0.0010.002
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 head0.051
GPT teacher head0.402
Teacher spread0.351 · 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 designQualitative
Domainnot available
GenreEmpirical

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

Citations1
Published2024
Admission routes1
Has abstractyes

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Same venueJournal of Forensic NursingSame topicTerrorism, Counterterrorism, and Political ViolenceFrench-language works237,207