Bibliographic record
Abstract
There is a revolution underway in the voluntary section in a number of overlapping arenas. After years of benign neglect government, political and academic attention has been directed to the information vacuum that surrounds this sector representing one eighth of Canada's Gross Domestic Product. Although a recent study revealed that Canadians hold a high degree of trust in the work and workers of charities, there is increasing pressure on voluntary organizations to articulate to their stakeholders all aspects of their accountability practices. Cognizant of this pressure, a concerned group from the voluntary sector established the Voluntary Sector Roundtable to look at its governance and accountability practices. Through a series of roundtable discussions with voluntary organizations across Canada the Voluntary Sector Roundtable developed eight key governance standards to act as a guide for the governance practices of voluntary boards. Despite the number of well-developed face-to-face training programs aimed at improving the governance practices of voluntary boards, the sheer size of the sector suggests that a technological solution in the form of online training will provide all boards the potential to access the training and information required to meet these emerging needs. The purpose of this survey was to discover and examine Canadian online training directed at voluntary boards. The study compared existing online training materials with the eight key standards developed by the Voluntary Sector Roundtable (the only existing standards of this nature in Canada). The study also closely compared existing online training to the key standards met by the Board Development Program text-based training materials.
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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".