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Record W2925288952 · doi:10.1177/1365480219832415

Student and staff social dynamics and transitions during school redesign

2019· article· en· W2925288952 on OpenAlexaffabout
Sejal Patel, Natalie Cummins

Bibliographic record

VenueImproving Schools · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Development and Social Support
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsFocus groupClosure (psychology)Qualitative researchNeighbourhood (mathematics)PedagogyDynamics (music)PerceptionSocial dynamicsPsychologyMathematics educationSociologyPolitical science

Abstract

fetched live from OpenAlex

This qualitative case study investigates student and school staff perceptions of transitions and changing social dynamics due to a temporary closure of an elementary school undergoing redesign in an inner-city neighbourhood in Toronto, Canada. Focus groups and interviews were conducted with 75 students (Kindergarten to Grade 8) and 28 staff who transitioned to two neighbouring schools during the school closure in 2011 and 2012. Students reported changes in their sense of belonging, incidents of bullying and violence, and student–student and student–teacher social dynamics during the transitional period. School staff also reported changing social dynamics among staff and students, the importance of strong leadership and teacher support during transitions and changes to school climate as a result of the transition. Suggestions and recommendations for future transitions associated with school redesign are discussed.

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)0.004
metaresearch head score (Gemma)0.007
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 score0.076
Threshold uncertainty score0.151

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0100.006
Scholarly communication0.0040.002
Open science0.0020.005
Research integrity0.0010.002
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 head0.010
GPT teacher head0.279
Teacher spread0.269 · 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

Citations4
Published2019
Admission routes2
Has abstractyes

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