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Record W7034064653

Strategies Leaders in a Canadian Charity Use to Maintain Donors’ Trust and Ensure Continued Donations

2022· article· en· W7034064653 on OpenAlexaboutno aff

Bibliographic record

VenueScholarWorks (Walden University) · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicParasite Biology and Host Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsMisappropriationAccountabilityDisadvantagedGovernment (linguistics)Transparency (behavior)AuditThematic analysisQualitative research
DOInot available

Abstract

fetched live from OpenAlex

Eroded public trust and financial support threaten charity organizations' sustainability. Charity directors are concerned with eroding trust as lack of confidence adversely impacts the economic lives of disadvantaged communities. Grounded in Stewart’s ladder of accountability theory and Alderfer’s existence, relatedness, and growth theory, the purpose of this qualitative single case study was to explore strategies charitable organizations’ leaders use to maintain donors’ trust and ensure continued donations. The participants were five charity directors who used strategies to maintain donors’ trust and ensure ongoing donations. Data were collected using semistructured interviews and document reviews. Through Braun and Clarke's six-step thematic analysis, six significant themes were identified: accountability, transparency, government funding, having good policies in place, meeting donors’ psychological needs to donate, and working with affiliated charities. A key recommendation for charity leaders is to adopt and maintain accountability and transparency best practices, including the availability and disclosure of annual independent audited financial statements to minimize scandals and misappropriation of funds, safeguard resources, maintain donors’ trust, and ensure continued donations. The implications for positive social change include the potential to implement charitable programs and activities to improve the local community's educational, social, and economic lives of disadvantaged people.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.560
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.262
Teacher spread0.244 · 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.

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

Citations0
Published2022
Admission routes1
Has abstractyes

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