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 provides a nuanced exploration of contemporary digital data governance, highlighting the importance of cooperation across sectors and disciplines in order to adapt to a rapidly evolving technological landscape. Most of the theory around global digital data governance remains scattered and focused on specific actors, norms, processes, or disciplinary approaches. This book argues for a polycentric approach, allowing readers to consider the issue across multiple disciplines and scales. \n \n \nPolycentrism, this book argues, provides a set of lenses that tie together the variety of actors, issues, and processes intertwined in digital data governance at subnational, national, regional, and global levels. Firstly, this approach uncovers the complex array of power centers and connections in digital data governance. Secondly, polycentric perspectives bridge disciplinary divides, challenging assumptions and drawing together a growing range of insights about the complexities of digital data governance. Bringing together a wide range of case studies, this book draws out key insights and policy recommendations for how digital data governance occurs and how it might occur differently. \n \n \nWritten by an international and interdisciplinary team, this book will be of interest to students and scholars in the field of development studies, political science, international relations, global studies, science and technology studies, sociology, and media and communication studies.
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 | 0.002 | 0.001 |
| Open science | 0.008 | 0.007 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.025 |
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