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Record W3008859347 · doi:10.1080/22423982.2020.1735052

School personnel and community members’ perspectives in implementing PAX good behaviour game in first nations grade 1 classrooms

2020· article· en· W3008859347 on OpenAlexafffundabout
Ellie M. Jack, Mariette Chartier, Gia Ly, Janique Fortier, Nora Murdock, Brooke Cochrane, Jonathon Weenusk, Roberta L. Woodgate, Gary Munro, Jitender Sareen

Bibliographic record

VenueInternational Journal of Circumpolar Health · 2020
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsCree Board of Health and Social Services of James BayFirst Nations Health and Social Secretariat of ManitobaUniversity of Manitoba
FundersCanadian Institutes of Health Research
KeywordsContext (archaeology)PsychologyFocus groupIntervention (counseling)Qualitative researchMental healthDevelopmental psychologyMedical educationSocial psychologyApplied psychologySociologyMedicinePsychiatryGeographySocial science

Abstract

fetched live from OpenAlex

First Nations peoples in Canada have a history of poor mental health outcomes, as the result of colonisation and the legacy of residential schools. The PAX Good Behaviour Game (PAX-GBG) is a school-based intervention shown to improve student behaviour, academic outcomes, and reduce suicidal thoughts and actions. This study examines the use of PAX-GBG in First Nations Grade 1 classrooms in Manitoba. Researchers collected qualitative data via interviews and focus groups from 23 participants from Swampy Cree Tribal Council (SCTC) communities. Participants reported both positive effects and challenges of implementing PAX-GBG in their classrooms. PAX-GBG created a positive environment where children felt included, recognised, and empowered. Children were calmer, more on-task, and understood the behaviours that are expected of them. However, for many reasons, PAX-GBG is not being used consistently across SCTC schools. Participants described barriers in implementation due to teacher turnover, lack of on-going training and support, developmental and behavioural difficulties of students, and larger community challenges. Participants provided suggestions on how to improve PAX-GBG to be a better fit for these communities, including important cultural and contextual adaptations. PAX-GBG has the potential to improve outcomes for First Nations children, however attention must be given to implementation within community context.

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)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.004
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 head0.115
GPT teacher head0.439
Teacher spread0.325 · 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 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

Citations11
Published2020
Admission routes3
Has abstractyes

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