Making Media Public: From Discussion to Action?
Bibliographic record
Abstract
By the summer of 2008, it had become clear that a crisis in media was under way in Canada. The media giant Canwest was teetering on the edge of bankruptcy, local television stations were being closed, thousands of media workers had been laid off, and community radio and television were barely supported. At the same time, publics linked through social networks were producing and distributing a growing range of their own content through new media. Old media had collided with new technologies, national policies were facing global political and economic challenges, and the need to develop new approaches to media models had become urgent. Although these questions were being debated in some communities—among academics, labour unions, media producers and policy activists, for example—in various media, and at the Canadian Radio-television and Telecommunications Commission (CRTC), we felt there was a pressing need to increase dialogue between and beyond these groups. For all of these reasons, we organized the Making Media Public conference. Our aim was to bring people together to critically assess the current media situation, to envision ways of building sustainable media models that address the experiences of diverse Canadians, and to increase public contributions to and dialogue about policymaking. The conference, held at York University from May 6 to 8, 2010, was designed to enable sustained analysis of the current media crisis and to gain insight into the challenges and opportunities for transforming media in Canada. We were able to bring together a range of publics that does not usually have opportunities to gather for discussion: academic researchers, media workers, policymakers, union members, community members, alternative media producers, students, and media educators. As academics and graduate students who have actively participated in the production of alternative media and policy engagement, our aim was to dissolve the boundaries between academic researchers and those involved in media production and policy development, both large-scale and community-based. We hoped the conference would
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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 | 0.085 | 0.105 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.076 | 0.093 |
| Scholarly communication | 0.071 | 0.082 |
| Open science | 0.010 | 0.041 |
| Research integrity | 0.065 | 0.068 |
| Insufficient payload (model declined to judge) | 0.027 | 0.005 |
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".