Caught Between Volunteerism and Professionalism: Support by Nonprofit Leaders for the Donative Labor Hypothesis
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
The rise of professionalism within the nonprofit sector has transformed the sector’s reliance on well-meaning volunteers to paid professionals. While the professionalization of the nonprofit workforce is likely to continue, nonprofits are increasingly challenged for their inability to pay competitive wages. Our study argues that a social expectation for nonprofit employees to forgo some of their wages influences the donative labor narrative, which in turn impacts low nonprofit wages. We present data from an online survey experiment of executive directors at 467 nonprofits, along with their organizations’ Form 990 filings, to contrast socially biased attitudes and genuine views toward the donative labor hypothesis. The findings illustrate that the donative labor narrative should be understood as a result of social expectations for sacrifice of nonprofit employees, rather than a simple outcome of supply and demand in the labor market. We discuss the need to reframe the widespread donative labor narrative.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it