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Standing on the Edge: How School Leaders Apply Restorative Practices in Response to Cyberbullying and Online Aggression

2015· article· en· W2508303908 on OpenAlex
Laurie Corrigan, Lorayne Robertson

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal for Digital Society · 2015
Typearticle
Languageen
FieldPsychology
TopicBullying, Victimization, and Aggression
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsAggressionPsychologyEnhanced Data Rates for GSM EvolutionSocial psychologyEngineering

Abstract

fetched live from OpenAlex

This paper summarizes findings about restorative practices as one aspect of a research study examining vice-principals' responses to harmful cyber events such as cyberbullying and online aggression. It also considers the school's moral and legislated role in responding to these events. It is theorized that these negative online interactions occur as a result of a lack of social regulation, social presence, and empathy. Three theories are considered in connection to cyber conflict and cyberbullying: Tompkins' affect theory; Braithwaite's re-integrative shame theory; and Rettie's social presence theory. The first two are key restorative practices theories while the third considers social presence in online learning environments. Findings indicate that schools are a nexus for online events where the intersection of these theories is evidenced in practice. Based on these findings, recommendations include deliberate consideration for introducing elements of social presence, online regulation, community building, and empathy before and responding to cyber events.

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.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.242
Threshold uncertainty score0.604

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.117
GPT teacher head0.406
Teacher spread0.289 · 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