Volunteers and the Economic Downturn
Bibliographic record
Abstract
The recent economic crisis has subjected America's nonprofit organizations to considerable fiscal stress. To find out more about the response of nonprofits to the recent economic climate, the Corporation for National and Community Service partnered with the Johns Hopkins Nonprofit Listening Post Project on a national survey of nonprofits and AmeriCorps sponsor organizations.The survey revealed that 80 percent of responding organizations experienced some level of fiscal stress between September 2008 through March 2009, when the downturn intensified, and that for close to 40 percent of them the stress was considered "severe" or "very severe." In response, nearly a quarter (23%) of nonprofits reported decreasing staff hours, a third reported eliminating staff positions, and 40 percent reported postponing the filling of new positions. At the same time, nearly three-fourths of the organizations reported they had maintained or increased the number of people their organizations served, and even among those reporting "severe" or "very severe" fiscal stress and resulting cutbacks in staff, 60 percent reported they had been able to maintain or increase the number of people their organizations served.
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.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.001 |
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".