The Rationalization of Charity: The Influences of Professionalism in the Nonprofit Sector
Bibliographic record
Abstract
This paper analyzes how professional values and practices influence the character of nonprofit organizations, with data from a random sample of 501 (c)(3) operating charities in the San Francisco Bay Area collected between 2003 and 2004. Expanded professionalism in the nonprofit world involves not only paid, full-time careers and credentialed expertise but also the integration of professional ideals into the everyday world of charitable work. We develop key indicators of professionalism and measure organizational rationalization as expressed in the use of strategic planning, independent financial audits, quantitative program evaluation, and consultants. As hypothesized, charities operated by paid personnel and full-time management show higher levels of rationalization. While traditional professionals (doctors, lawyers, and the clergy) do not differ significantly from executives with no credentialed background in eschewing business-like practices, managerial professionals champion such efforts actively, as do semi-professionals, albeit more modestly. Management training is also an important spur to rationalization. We assess what is gained and lost and the tension that can arise when nonprofits become professionalized and adopt more methodical, bureaucratic procedures.
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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 | 0.007 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".