Bibliographic record
Abstract
Campaigners against corruption advocate transparency as a fundamental condition for its prevention. Trans-parency in itself is not the most important thing: it is the accountability that it makes possible. Transparency itself is, in fact, a metaphor based on the ability of light to pass through a solid, but transparent, medium and reveal what is on the other side. In practice it allows the revelation of what otherwise might have been concealed, and it is applied in a social context to the revelation of human activity in which there is a valid public interest. It can be applied to all of those who hold power and responsibility, whether that is political or economic. More accurate definition of the term, including distinctions between open governance, procedural transparency, radical transparency, and systemic or total transparency is important. Various ways in which an observer can make use of transparency to scrutinise the activity of others, including freedom of information laws, accounting and audit systems, and the protection of public interest disclosure (whistleblowing) also need to be distinguished from each other.
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 | 0.020 | 0.084 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.006 | 0.043 |
| Scholarly communication | 0.015 | 0.023 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.006 | 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".