Bibliographic record
Abstract
Access to information (ATI) and freedom of information (FOI) mechanisms are now relevant features of governments in many liberal democracies today. Citizens, organizations, and permanent residents in several countries across the globe can request unpublished information from federal, provincial, state, county, and municipal government agencies. However, most qualitative researchers appear to be unfamiliar with ATI/FOI or write it off as an approach used by journalists rather than as a way to systematically produce qualitative and longitudinal data about government practices. In this article, the authors discuss the use of ATI/FOI requests as a means of data production. The authors show how the use of ATI/FOI requests intersects with issues such as reflexivity, the Hawthorne effect, interviewing, and discourse analysis. The study objective is to foster a multidisciplinary discussion of the strengths and weaknesses of ATI/FOI requests as a data production tool.
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 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 | 0.048 | 0.136 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.007 | 0.046 |
| Scholarly communication | 0.017 | 0.021 |
| Open science | 0.001 | 0.014 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".