Attribution and Motivation: Gender, ethnicity, and religion differences among Indonesian university students
Bibliographic record
Abstract
The study explores the possibilities of gender, ethnicity, and religion differences on attributions (locus of control, stability, personal and external control), motivational goals (learning, performance approach, performance avoidance, and work avoidance), self-efficacy, intelligence beliefs, religiosity, racial/ethnic identity, and academic performance (mid-term test, final test, and GPA scores) within the Indonesian university settings. Racial/ethnic identity had three dimensions: private regard, ethnic importance, and social embeddedness; whilst religiosity had two dimensions: religious behaviour and intrinsic religiosity. 1,006 students (73.8% Native Indonesians and 24.8% Chinese Indonesians) from three public and two private universities participated. Significant gender differences were found on work avoidance goals. Ethnic and religion differences were found on religiosity. Gender and religion interactions resulted significant differences on attribution (locus of control), religiosity (intrinsic religiosity), and academic performance (final test score).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".