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Record W2946145027 · doi:10.22230/cjnser.2019v10n1a273

Trust and transparency: Accreditation and impact reporting by Canadian charities

2019· article· en· W2946145027 on OpenAlexaffvenueabout
Christopher N. Dougherty

Bibliographic record

VenueCanadian journal of nonprofit and social economy research · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicNonprofit Sector and Volunteering
Canadian institutionsCarleton University
Fundersnot available
KeywordsAccreditationPolitical scienceAccountingTransparency (behavior)Public relationsWelfare economicsPublic administrationBusinessEconomicsLaw

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.225
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.089
GPT teacher head0.387
Teacher spread0.298 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2019
Admission routes3
Has abstractyes

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