Trust and transparency: Accreditation and impact reporting by Canadian charities
Bibliographic record
Abstract
This article examines the public reporting of impact, defined as progress towards a charity’s mission and long-term objectives, by Canadian charities through their annual reports. The public reporting behaviour of those accredited under Imagine Canada’s Standards Program is compared with a matched sample of charities that have not sought accreditation. The objective is to explore whether trust-building activities like public disclosures of impact and third-party accreditation are convergent. The study finds that accreditation status correlates with impact measurement and reporting; both trends are linked to organizational size, and accreditation does not appear to be causing charities to increase their disclosures of impact, which suggests that there may be underlying factors driving both behaviours. These findings generally affirm earlier research that correlates organizational size with impact measurement, adding that the effect is weak.Cet article examine comment les associations caritatives canadiennes, dans leurs rapports annuels, rendent compte de leur impact, c’est-à-dire de leur progrès par rapport à leur mission et à leurs objectifs à long terme. Cette étude compare les comptes rendus d’associations accréditées par le Programme de normes d’Imagine Canada avec un échantillon apparié d’associations qui n’ont pas été accréditées. L’objectif est de déterminer s’il y a convergence parmi les démarches entreprises pour gagner la confiance du public telles que l’accréditation par un tiers et la divulgation d’impact. Cette étude observe que les associations accréditées sont plus enclines à mesurer et à divulguer leur impact; que ces deux pratiques sont plus communes dans les grandes associations; et que l’accréditation à elle seule n’entraîne pas forcément les associations caritatives à divulguer leur impact, ce qui suggère que des facteurs sous-jacents sont peut-être responsables pour les deux pratiques. En général, ces conclusions confirment des recherches antérieures trouvant une corrélation entre la grandeur d’un organisme et le désir de mesurer son impact, bien que ce lien semble être faible.
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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 | 0.014 | 0.075 |
| 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 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".