The Right Stuff: Are Not-For-Profit Managers Really Different?
Bibliographic record
Abstract
ABSTRACT In response to public pressure for accountability in the not-for-profit (NFP) sector, attempts have been made to adopt for-profit controls. These have generated mixed results. While many have argued that employees attracted to the NFP sector are “different,” little prior empirical evidence backs up this claim. To address this gap, we review the literature to identify claimed individual characteristics that might differ and use the survey method to examine whether these differences exist between the groups of responding managers working in the NFP and for-profit sectors. NFP respondents exhibit lower levels of narcissism, lower levels of entitlement, less extroversion, and a more externally oriented locus of control than their for-profit counterparts. In exploratory multivariate analysis, best predictors of NFP membership include extroversion, locus of control, conscientiousness, and moral reasoning. Rather surprisingly, the groups did not differ on altruism or tolerance for ambiguity. Implications for control system design are discussed.
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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 | 0.006 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".