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Record W3105434297 · doi:10.3233/wor-203310

School quality of life: Cross-national comparison of students’ perspectives

2020· article· en· W3105434297 on OpenAlexaffabout
Asnat Bar-Haim Erez, Stefan Kuhle, Jessie‐Lee D. McIsaac, Naomi Weintraub

Bibliographic record

VenueWork · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsMount Saint Vincent UniversityDalhousie University
Fundersnot available
KeywordsPsychosocialAffect (linguistics)Quality of life (healthcare)PsychologyPerceptionMedical educationQuality (philosophy)GerontologyMedicineClinical psychologyDevelopmental psychologyNursingPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Cross-national comparisons of students' school quality of life (QoL) can support our understanding of factors that may affect students' health and well-being at school. OBJECTIVE: To compare Canadian and Israeli students' perception of their school QoL. METHODS: The Quality of Life at School Questionnaire (QoLS) was administered to 1231 students in 4th to 6th grades from Canada (n = 629) and Israel (n = 602), measuring: Physical Environment, Positive Attitudes, Student-Teacher Relationship, and Psychosocial. RESULTS: The Canadian students scored significantly higher than the Israeli students on all domains. The two-way ANOVA did not show a statistically significant interaction between country and gender nor age. However, within each country, girls and 4th grade students reported higher overall QoLS. CONCLUSIONS: This study lends support for the universal aspects of perceived QoL at school. This information may serve clinicians and educators in setting goals and developing programs to enhance students' school QOL.

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)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.088
Threshold uncertainty score0.809

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.119
GPT teacher head0.478
Teacher spread0.359 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations9
Published2020
Admission routes2
Has abstractyes

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