Bibliographic record
Abstract
Access to information is a bedrock principle of contemporary democratic governments and their public agencies and entities. Access to information depends upon these public institutions to document their activities and decisions. When public institutions do not document their activities and decisions, citizens’ right of access is ultimately denied. Public accountability and trust, in addition to institutional memory and the historical record, are undermined without the creation of appropriate records. Establishing and enforcing a duty to document helps promote accountability, openness, transparency, good governance, and public trust in public institutions. A duty to document should therefore be a fundamental component of access to information legislation and records and information management practices.This article begins a discussion on the concept and practice of a duty to document. Using Canada as a case study, this article's main aim is to help illuminate the importance and implications of a duty to document in both access laws and records and information management policies to help ensure good governance practices.
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 | 0.027 | 0.081 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.033 |
| Scholarly communication | 0.016 | 0.017 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.013 | 0.010 |
| Insufficient payload (model declined to judge) | 0.015 | 0.010 |
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".