Sharing Data and Results with Study Participants: Report on a Survey of Cultural Anthropologists
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A FIRST-EVER SURVEY of cultural anthropologists was conducted concerning the sharing of data, interpretations, and results with study participants. Briefly summarized, the study showed that almost all of the survey respondents had shared data or results with participants and almost all found this to be a positive experience. They had carried out research in many countries, some over long periods of time, and many had completed several field projects. Most believe that researchers, either alone or in consultation with participants and their groups, should decide whether, when, and what to share. Anthropologists find that sharing produces many benefits, for themselves as individuals and as researchers, for individual participants, and for the communities, groups, or institutions to which the latter belong. The perceived harms that might result from sharing have to do particularly with potential threats to privacy, confidentiality or anonymity, as well as the possibilities of social conflict and oppression. Thus, researchers have serious concerns about the sharing of certain kinds of data that might lead to such consequences. While many or most respondents think that sharing is the ethically proper course of action, they are very aware of the complexities of particular situations and the need for nuanced decision making. Most think that the researcher should play a major role in deciding whether sharing should take place and what should be shared. Hence, for these cultural anthropologists, in the end, sharing requires trying to balance the good of sharing with the good of doing no harm to those with whom they have done research.
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Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | MetaresearchOpen science Domain: Reproducibility · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
| gpt | Metaresearch Domain: Reproducibility · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
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 | 0.164 | 0.246 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.031 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.014 |
| 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 it