Crafting Preliminary Model for Mosque Cooperatives’ Antecedents of Performance
Bibliographic record
Abstract
This paper explored the determinants of performance of mosque cooperatives in Malaysia. Questionnaires were distributed among mosque co-operators in the state of Selangor, Negeri Sembilan, and Kuala Lumpur. Forty-one questionnaires were returned and found fit for further analysis using Partial Least Square (PLS) method. The findings postulated three determinants of mosque cooperatives’ performance viz. board members’ characteristic, internal supervision and monitoring, and members’ support. The antecedents of mosque cooperative performance initial model also met the requirement for convergence validity, discriminant validity, and reliability. The PLS result showed that board members’ characteristics, members’ support, and internal supervision and monitoring positively determined mosque cooperatives’ financial performance, and eventually financial performance influenced non-financial performance. The findings are expected to benefit regulator, national apex cooperative (ANGKASA), and mosque co-operators in illustrating an appropriate mechanism to boost performance in coming years.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".