Bibliographic record
Abstract
<h3>Objective</h3> The conversations in accountability were designed to gain an understanding of the use and changes to accountability in charities over time, including learning how results are measured. <h3>Methods</h3> As part of a larger study which investigated accountability in charities working to reduce mortality of children younger than 5 years in least developed countries, a multiple-case study comprising semistructured in-depth key informant interviews was conducted to investigate the use and effects of accountability in three charities of differing sizes. <h3>Results</h3> Smaller charities tend to use fewer accountability mechanisms than larger ones, whereas the variation in their use between small and medium-sized charities is greater than the variation between medium-sized and large charities. <h3>Conclusion</h3> Although accountability has changed over time, charities believe that they are providing the correct amount of accountability – that is, enough to satisfy the perceived demands of their stakeholders but not so much that it detracts from the mission or incurs costs in excess of benefits. However, the tools to determine effectiveness and impact are lacking.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".