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Record W2997689740 · doi:10.1177/0190272519876936

Conflict as a Social Status Mobility Mechanism in Schools: A Network Approach

2020· article· en· W2997689740 on OpenAlexfundno aff
Laura M. Callejas, Hana Shepherd

Bibliographic record

VenueSocial Psychology Quarterly · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsnot available
FundersCanadian Institute for Advanced ResearchSpencer FoundationRussell Sage FoundationNational Science Foundation
KeywordsBetweenness centralitySocial psychologyPsychologyDominance (genetics)Conflict theoriesSocial statusCentralityMechanism (biology)Group conflictSocial conflictSocial network (sociolinguistics)Conflict resolutionSociologyPolitical scienceSocial sciencePolitics

Abstract

fetched live from OpenAlex

Participating in conflict may facilitate the acquisition of social status in a group. We build on theories about the sources of conflict and status to formulate propositions about how conflict affects status mobility in schools. Using two-wave panel data from over 20,000 students in 56 middle schools, we first examine the relationship between change in conflict with schoolmates and change in a network-derived metric of status, betweenness centrality, which is an indicator of being well known. More overall conflict with students is associated with increases in status up to a threshold. Additionally, students who perceive more conflict with others who do not perceive conflict in return also gain status. Finally, more conflict with friends does not increase status. Based on this evidence, we propose a mechanism by which conflict increases status through signaling integration in the school’s social scene rather than through establishing dominance over others, as previous literature suggests.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.317
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.070
GPT teacher head0.390
Teacher spread0.321 · 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 teacher head, not a consensus.

Study designTheoretical or conceptual
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

Citations7
Published2020
Admission routes1
Has abstractyes

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