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Record W7132870495

Exploring differences in achievement motivation in a diverse sample of Canadian students

2004· dissertation· W7132870495 on OpenAlexaboutno aff
Nadine Marcia Dechausay

Bibliographic record

VenueTSpace · 2004
Typedissertation
Language
FieldPsychology
TopicEducation, Achievement, and Giftedness
Canadian institutionsnot available
Fundersnot available
KeywordsAcademic achievementSample (material)Need for achievementEthnic groupEmpirical researchPositive relationshipLongitudinal study
DOInot available

Abstract

fetched live from OpenAlex

This study examined the relationship between achievement motivation and academic performance, as well as factors predicting these variables, in a diverse sample of 12--15 year old Canadian students. A total of 4,237 students of East Asian, South Asian, Native, African Canadian, and Euro Canadian backgrounds were included in analyses using data from the National Longitudinal Survey of Children and Youth. In general, this study provides modest support for achievement motivation theories, and empirical evidence that Native and African Canadian students may be at-risk with respect to motivation and achievement. The results confirmed a positive correlation between achievement motivation and academic performance. Significant mean differences in achievement motivation and academic performance were found between ethnocultural groups, with East and South Asian students showing the highest outcomes on these measures, and Native and African Canadian students showing the lowest. Positive correlations were found between achievement motivation and several theoretically-meaningful predictor variables.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.027
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.003
Science and technology studies0.0060.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.209
GPT teacher head0.405
Teacher spread0.196 · 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 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

Citations0
Published2004
Admission routes1
Has abstractyes

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