Bibliographic record
Abstract
This study investigates the use of five broad accountability mechanisms by gathering the perceptions of charities involved in the Canadian effort to reduce under-5 mortality abroad. While annual deaths in children under the age of 5 declined from an estimate of over 24.0 million in 1960 to under 8.0 million in 2010, mortality reduction goals have been established and missed for decades. As worldwide economies worsen, the amount of funds available for development assistance can be expected to decrease. This study seeks to determine if having accountability mechanisms is perceived to improve organizational behaviour, results and/or reduce costs. It uses a mixed methods approach including: a literature review to gain an understanding of accountability, effectiveness, development and under-5 mortality; key informant interviews to gain an understanding of funders, charities and development; a survey to gather the information required to answer the research questions; and a multiple-case study to gain a better appreciation of how accountability is used and to gather evidence of survey responses. The study investigates: which accountability mechanisms charities have, why they have them and the associated accountability holders; standards body memberships; the relationship between accountability mechanisms and various organizational characteristics; and the perceived effects of accountability mechanisms on organizational behaviour, results and costs. The survey finds that: charities say that they adopt accountability mechanisms because it is a good management practice that is perceived to improve organizational behaviour and results while not incurring costs in excess of the benefits; charities are more likely to adopt accountability mechanisms due to internal pressures than external pressures; the use of accountability mechanisms increases with organization size; and there is a greater difference in use of accountability mechanisms between small and large charities than there is between medium and large charities. The multiple-case study confirms the survey results. This study fills a gap in the literature by providing a Canadian perspective on the use of accountability mechanisms and the relationships amongst them and their perceived effects on organizational behaviour, results and costs. As economic burdens increase, increased accountability may lead to improved results even with fewer dollars.
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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 | 0.013 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".