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
Preface Karen Fogg, Director Secretary-General, International IDEA Introduction Marian Sawer, Manon Tremblay and Linda Trimble Part 1: The Descriptive Representation of Women 1. Australia: Ian McAllister, Australian National University 2. Canada: Lisa Young, University of Calgary 3. New Zealand: Elizabeth McLeay, Victoria University of Wellington 4. The United Kingdom: Donley T. Studlar, West Virginia University Part 2: The Substantive Representation of Women 5. Australia: Marian Sawer, Australian National University 6. Canada: Linda Trimble, University of Alberta 7. New Zealand: Sandra Grey, Victoria University of Wellington 8. The United Kingdom: Sarah Childs, University of Bristol Part 3: New Institutions, New Opportunities? 9. Northern Ireland: Yvonne Galligan, Queen's University, Belfast 10. Scotland: Fiona Mackay, University of Edinburgh 11. Wales: Paul Chaney, Cardiff University 12. Nunavut: Manon Tremblay and Jackie Steele, University of Ottawa Conclusion: Jennifer Curtin, Monash University
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.
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) | 0.001 | 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