Organizational Characteristics and Disclosure Practices of Non-profit Organizations in Malaysia
Bibliographic record
Abstract
The purpose of this study is to examine the influence of organizational characteristics on the extent of disclosures in the annual reports of non-profit organizations (NPO) in Malaysia. Organizational characteristics and the extent of disclosures are obtained from the content analysis of annual reports of 213 NPOs registered with Registrar of Societies in Malaysia for the financial period 2010. This study provides evidence that the overall extent of disclosure is low. Of the organizational characteristics, this study revealed significant positive relationships between size and some types of funds available to the NPOs. The significant positive relationships between certain types of funds and extent of disclosures in some parts of the annual reports indicate selective disclosure strategies by non-profit managers, thus reducing meaningful transparency in the non-profit sector. Nevertheless, it indicates that non-profit managers are using disclosures in annual reports in managing their inter-organizational relationships in ensuring continuous flow of resources to their organisations.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".