Bibliographic record
Abstract
Abstract This collection brings together strategies for advancing media reform objectives, prepared by 33 scholars and activists working in and/or studying in more than 25 countries, including: Canada, Mexico and the United States; Argentina, Bolivia, Brazil, Chile, Colombia, Ecuador, Guatemala, Uruguay, and Venezuela; Iceland; Germany, Switzerland and the UK; Burma/Myanmar, Taiwan, Thailand and the Philippines; Egypt, Ghana, Israel and Qatar. Contributors first presented their ideas in the summer of 2013 at a preconference of the International Communication Association, hosted by Goldsmiths, University of London in the UK. The goal then, as it is now, was to bring together successful and promising strategies for media reform to be shared across international lines and media reform contexts. The editors and authors hope this volume will serve as a useful resource for scholars and activists alike, looking to better understand the concept of media reform, and how it is being advanced around the world. The book is organized into four sections: contexts, digital activism, media reform movements, and media reform in action. It opens with a consideration of some theoretical approaches to media reform while the digital activism section includes chapters that present a range of strategies that media reformers might want to consider. The section on media reform movements includes examples from across the globe and highlights a variety of online and offline strategies to achieve change. The final section consists of short chapters submitted by activist organizations that include a description of their mission and examples of successful strategies employed in the pursuit of media reform goals.
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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.007 | 0.015 |
| Scholarly communication | 0.016 | 0.020 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.033 | 0.008 |
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".