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Record W220182117 · doi:10.3138/cjpe.17.001

Improving Social Policy with National Data: A Comparison of Social Support for Students Among Canadian Provinces

2002· article· en· W220182117 on OpenAlexaffvenueabout
Xin Ma

Bibliographic record

VenueCanadian Journal of Program Evaluation · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsSocioeconomic statusSocial supportProsocial behaviorPsychologyEmotional supportCensusImmigrationMultilevel modelSurvey data collectionSocial psychologyDemographyGeographySociology

Abstract

fetched live from OpenAlex

Abstract: The purpose of this study was to examine social support for students as it related to individual and provincial characteristics in Canada, with data from the National Longitudinal Survey of Children and Youth and census data. The data included 7,648 students aged 8 to 11 years from 10 provinces. Factor analysis indicated two latent factors underlining social support for students: perceived personal support and perceived institutional support. Results of hierarchical linear modelling show that perceived personal support did not fluctuate with provincial characteristics. Students who were immigrants to Canada, with low socioeconomic status (SES), and with poor prosocial behavior perceived less personal support. Students in provinces with higher birth rates perceived less institutional support. SES and family size had strong effects on perceived institutional support in some provinces but weak effects in other provinces. Students from both-parent households, with emotional problems, and from large families perceived less institutional support.

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)0.001
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 score0.412
Threshold uncertainty score0.982

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.232
GPT teacher head0.505
Teacher spread0.273 · 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

Citations3
Published2002
Admission routes3
Has abstractyes

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