Director Monitoring of Expense Misreporting in Nonprofit Organizations: The Effects of Expense Disclosure Transparency, Donor Evaluation Focus and Organization Performance
Bibliographic record
Abstract
Abstract This study examines whether three factors—the transparency of expense disclosures, donor evaluation focus, and organization performance—influence how directors monitor management expense misreporting in nonprofit organizations. An experiment with 189 nonprofit directors finds that the enhanced transparency of expense disclosures increases director monitoring by reducing the tendency to accept management expense misreporting. Further, an organization's nonfinancial performance and the perceived fairness of donor evaluation focus interact to influence director monitoring practices. Specifically, when directors know an organization's nonfinancial performance is poor and understand that this performance will negatively influence the willingness of donors to contribute, directors monitor less if they think that donors are adopting a more balanced approach to organizational evaluation that focuses on both financial and nonfinancial performance; that is, there is a reverse fair process effect as this donor approach is perceived as being fairer than if donors focus solely on financial performance. However, monitoring is equally strong regardless of donor evaluation focus when directors know that an organization's nonfinancial performance is good and a donation is forthcoming.
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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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| 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".