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Record W3196009259 · doi:10.1037/spq0000445

Using social network position to understand early adolescents’ power and dominance within a school context.

2021· article· en· W3196009259 on OpenAlexfundaboutno aff
Naomi C. Z. Andrews, Hannah McDowell, Natalie Spadafora, Andrew V. Dane

Bibliographic record

VenueSchool Psychology · 2021
Typearticle
Languageen
FieldPsychology
TopicBullying, Victimization, and Aggression
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPrestigePopularityDominance (genetics)PsychologySocial network (sociolinguistics)FriendshipSocial psychologyCentralityReputationPeer groupPower (physics)Social statusSociologyPolitical scienceSocial scienceSocial media

Abstract

fetched live from OpenAlex

= 466, 51% girls, 63% White) in southern Ontario, Canada. Peer nominations were used to assess social network centrality and prestige (via friendship nominations), social power strategies (coercive and cooperative strategies), social power, and peer reputation (popularity and likeability). Results indicated that coercive and cooperative strategies were used by youth high in both centrality and prestige, but that only high prestige related to power, popularity, and likeability. Results have implications for the usefulness of a social networks approach to understanding the structure of youths' social relationships and power in school settings, as well as practical implications for teachers and other school staff. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.783
Threshold uncertainty score0.437

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.036
GPT teacher head0.344
Teacher spread0.308 · 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 designObservational
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

Citations17
Published2021
Admission routes2
Has abstractyes

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