Public benefits or private? The case of the Canadian Media Research Consortium. Canadian Journal of Communication. Forthcoming
Bibliographic record
Abstract
Commission established its Public Benefits program in the late 1970s. It eventually came to re-quire a minimum 10 percent of the value of acquired broadcasting licences to be devoted to worthwhile initiatives. A portion of a CAD $230-million Public Benefits package in 2000 was devoted to funding a Canadian Media Research Consortium (CMRC) established between sev-eral universities. Mandated to “focus on the development of Canadian data for use in media planning, ” the CMRC issued its first report in 2003, which was criticized for flawed methodol-ogy and cited as an example of “administrative ” marketing research performed to the benefit of media owners rather than to the benefit of the public. The CMRC issued a five-year retro-spective study in 2008 that addressed some of the earlier methodological flaws and perhaps, as a result, reached different conclusions.
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 | 0.045 | 0.084 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.011 |
| Science and technology studies | 0.048 | 0.037 |
| Scholarly communication | 0.036 | 0.025 |
| Open science | 0.005 | 0.011 |
| Research integrity | 0.024 | 0.011 |
| Insufficient payload (model declined to judge) | 0.011 | 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".