ERIC ED477401: Job Quality in Non-Profit Organizations. CPRN Research Series on Human Resources in the Non-Profit Sector.
Bibliographic record
Abstract
The quality of jobs in nonprofit organizations in Canada was examined through a review of data from Canada's Workplace and Employer Survey, which collected data from a nationally representative sample of Canadian workplaces and paid employees in those workplaces. Key findings of the analysis were as follows: (1) overall, compared to the for-profit sector and nonprofit organizations in "quasi-public" industries (termed the "quango sector"), the nonprofit sector employs larger proportions of workers on a temporary or part-time basis; (2) average hourly earnings of managers, professionals, and technical/trades workers in the nonprofit sector lag behind those of their counterparts in the for-profit and quango sectors; (3) only a minority of non-profit employers offer benefits such as medical insurance; (4) approximately two-thirds of employees of non-profits reported that they were satisfied with both their job and overall pay and benefits, which was similar to the percentage in the quango sector and slightly lower than that in the for-profit sector; (5) only 63% of nonprofit sector employees over age 45 were satisfied with both their pay and benefits compared with 75% of employers over age 45 in the for-profit sector; and (6) many paid employees in the nonprofit sector were women with postsecondary credentials. (Thirty-one tables/charts are included. The bibliography lists 43 references.) (MN)
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 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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.054 | 0.004 |
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; both teacher heads agree on what is shown here.
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".