Reporting Volunteer Labour at the Organizational Level: A Study of
Bibliographic record
Abstract
Volunteer contributions in the production of services are an important resource internationally. However, few countries include volunteer contributions in their national accounts, even though many encourage their populations to engage in volunteering. At the organizational level, many nonprofit organizations using volunteers often limit their input to a footnote in annual reports acknowledging their contribution; few estimate their value in financial terms. As a result, their financial accounts lack information upon which to base decisions affecting the organizations and the communities they serve. Additional information is required to assess the impact of volunteers in individual nonprofits as well as the sector as a whole. This study focuses on Canada, one of the few countries that include volunteers in the national accounts, to examine to what extent nonprofit organizations estimate a financial value for these contributions and include this in their financial statements. This paper reports the results of an online survey of 661 nonprofits from across Canada. In order to understand why some organizations keep records for volunteer contributions and quantify them, two sets of explanatory factors are explored: organizational characteristics and the attitude of the executive director. We find larger organizations were more likely to engage in record keeping and estimating volunteer value, as were organizations with a relatively large group of volunteers and volunteer programs. The attitude of the
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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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 teacher head, 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".