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Record W2760753917 · doi:10.1177/0829573517732202

The Who, What, and Where of School Kindness: Exploring Students’ Perspectives

2017· article· en· W2760753917 on OpenAlexaff
John-Tyler Binfet, Holli‐Anne Passmore

Bibliographic record

VenueCanadian Journal of School Psychology · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsUniversity of British Columbia, Okanagan CampusKelowna General HospitalUniversity of British Columbia
Fundersnot available
KeywordsKindnessProsocial behaviorPsychologyContext (archaeology)Social psychologyTheology

Abstract

fetched live from OpenAlex

The aim of this exploratory study was to examine fourth to eighth graders’ conceptualizations of kindness at school (i.e., their definition of kindness, an example of an act of kindness they have done, who they see as the most salient adult agent of kindness, and which location they deem that kindness happens most). To date, kindness research has focused predominantly on assessing the effects of being kind on student well-being and little is known about how students understand kindness and are kind in school. Across definitions and examples of kindness, the themes of helping others, showing respect, and encouraging others were prevalent. Teachers and principals were identified as the main adult agents of kindness; the classroom and outside/playground were identified as the two main kindness locations. Understanding how students conceptualize kindness within the school context holds implications for educators seeking to foster prosocial behavior among students.

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)0.005
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0070.009
Scholarly communication0.0080.005
Open science0.0010.005
Research integrity0.0010.004
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 head0.099
GPT teacher head0.401
Teacher spread0.303 · 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

Citations45
Published2017
Admission routes1
Has abstractyes

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