MétaCan
Menu
Back to cohort
Record W2029354149 · doi:10.1177/0829573509332243

Self-Beliefs and Behavioural Development as Related to Academic Achievement in Canadian Aboriginal Children

2009· article· en· W2029354149 on OpenAlexaffabout
Lola Baydala, Carmen Rasmussen, June Birch, Jody Sherman, Erik Wikman, Julianna Charchun, Merle Kennedy, Jeffrey Bisanz

Bibliographic record

VenueCanadian Journal of School Psychology · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsSimon Fraser UniversityUniversity of Alberta
Fundersnot available
KeywordsPsychologyAcademic achievementPsychological interventionIndigenousDevelopmental psychologyTest (biology)Standardized testAchievement testIntelligence quotientWechsler Adult Intelligence ScaleCognitionMathematics education

Abstract

fetched live from OpenAlex

The authors explored the relationship between measures of self-belief, behavioural development, and academic achievement in Canadian Aboriginal children. Standardized measures of intelligence are unable to consistently predict academic achievement in students from indigenous populations. Exploring alternative factors that may be both predictive and amenable to improvements with interventions is therefore important in order to address the growing educational disparity in Canadian Aboriginal children. In this study, significant correlations were found between the Self-Perception Profile for Children rating of behavioural conduct and close friendships, the Behavior Assessment Scales for Children ratings of leadership and study skills, and the Wechsler Individual Achievement Test measures of academic achievement. A school environment that provides opportunities for developing social skills and creating friendships as well as culturally appropriate interventions that support the development of leadership and study skills may provide Canadian Aboriginal children with the tools they need to achieve academically.

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)0.001
metaresearch head score (Gemma)0.000
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 score0.513
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.017
GPT teacher head0.357
Teacher spread0.340 · 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

Citations23
Published2009
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of School PsychologySame topicEarly Childhood Education and DevelopmentFrench-language works237,207