Does Trust Matter? Uncovering the Conditions by Which Boards Trust Managers in Nonprofits
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Do nonprofit boards need to trust their managers in the absence of performance data about the intangible social goals promised in their mission? We found that nonprofit boards impose conditions not directly related to organizational performance to assess if they can trust their managers. These conditions focus on both managers’ actions and board actions. For example, boards trust their managers more when managers exhibit the types of skills, experience, and networks the boards believe are needed to effectively run the nonprofits, and when managers provide the type and quality of information desired by board members. Boards also trust their managers when they believe they have effectively recruited managers with the desired abilities, and have an aspirational belief that they can effectively assess manager performance despite gaps in data. However, trust in their managers has less influence on board behavior when nonprofit boards assess how well their organizations have achieved their intangible social goals, as these assessments do not appear to be influenced by the trust relationship. Our study contributes to practice by encouraging open dialogue between boards and managers to address how boards can trust their managers despite an inability to rigorously monitor performance.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it