Independent Voices: Third Sector Media Development and Local Governance in Saskatchewan
Bibliographic record
Abstract
This dissertation examines nonprofit, co-operative, and volunteer media enterprises operating outside Saskatchewan’s state and commercial media sectors. Drawing on historical research and contemporary case studies, I take the position that this third sector of media activity has played, and continues to play, a much-needed role in engaging marginalized voices in social discourse, encouraging participation in community-building and local governance, fostering local-global connectedness, and holding power to account when the rights and interests of citizens are jeopardized. The cases studied reveal a surprising level of resiliency among third sector media enterprises; however, the research also finds that the challenges facing third sector media practitioners have deepened considerably in recent decades, testing this resiliency. A rapid withdrawal of media development support from the public sphere has left Saskatchewan’s third sector media at a crossroads. The degree of the problem is largely unknown outside media practitioner circles, even among civil society allies. I argue this relates to the lack of recognition of nonprofit, co-operative, and volunteer media as a distinct third sector, thus obscuring the global impact when hundreds of small undertakings shed staff and reduce operations in multiple locations across Canada. At the same time, there is increasing recognition that such media have the potential to fill a void left by commercial and state media organizations that have retreated from local communities. Accordingly, this dissertation makes the case for a coordinated media development strategy as a component of the social economy. The challenge is to build useful mechanisms of support among civil society allies that do not replicate oppressive donor-client relationships that are all too common in the arena of governmental and private sector support. While never simple, the opportunities and social benefits are considerable when citizens devise the means to participate in the creation of a robust, diverse media ecology.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".