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
This book examines how participants in governance and public affairs use data and information in defining public problems and their solutions. It is based on 18 in depth interviews with various kinds of participants in the public realm in Canada and the UK, from legislators, interest group representatives, journalists and civil servants. Responses are examined against the backdrop of two classical perspectives on decision making. It explores the types of data respondents emphasized in their work and what model of decision-making best reflected the realities of defining problems and selecting solutions in governance. The book demonstrates how there is a significant interplay between the long- and short-term aspects of governance. Narratives and data are inextricably intertwined in governance. The book explores the role of narratives in linking portrayals of the public good to problem definition and solution creation. It presents practical insights on how to approach generating and using data for the guidance of governing decisions, the implications of various kinds of research designs and for the normative practice of governance.
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 | 0.000 | 0.001 |
| 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 | 0.003 | 0.003 |
| 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