MétaCan
Menu
Back to cohort

The terrifying abyss of insignificance

2021· article· en· W3137517362 on OpenAlexaff
Luke Billingham, Keir Irwin‐Rogers

Bibliographic record

VenueOñati Socio-legal Series · 2021
Typearticle
Languageen
FieldPsychology
TopicBullying, Victimization, and Aggression
Canadian institutionsQuest University Canada
Fundersnot available
KeywordsInsignificanceCommitAffect (linguistics)Government (linguistics)CriminologyPsychologySociologySocial psychologyGender studies

Abstract

fetched live from OpenAlex

The concept of mattering can be helpful for understanding the ways in which structural and historical factors affect individual psychologies. This paper lays out the usefulness of mattering as a lens through which to examine why a small minority of young people in Britain commit violent acts. We first explore what it means to matter and the evidence linking the quest to matter with violence, and then examine the factors in contemporary Britain which can diminish a young person’s sense of mattering, using recent community research. We then critique the British government’s attempt to address the problem of violence through Gang Injunctions and Knife Crime Prevention Orders. We conclude by suggesting that policy-makers could gain substantial insight from investigating the connections between marginalisation, mattering and violence, rather than focusing disproportionately on the music young people choose to listen to or create, or the specific weapon that they opt to carry.

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)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0050.058
Scholarly communication0.0050.006
Open science0.0010.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.019
GPT teacher head0.288
Teacher spread0.270 · 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 designTheoretical or conceptual
Domainnot available
GenreCommentary

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

Citations23
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueOñati Socio-legal SeriesSame topicBullying, Victimization, and AggressionFrench-language works237,207