How Canadians Communicate IV: Media and Politics
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
In June 1980, in the wake of the Québec referendum on sovereignty and the 1979 and 1980 federal elections, the Reader's Digest Foundation and what was then Erindale College of the University of Toronto co-sponsored a conference on politics and the media. 1 The Erindale conference brought together prominent party strategists and organizers, journalists, and scholars.Participants spoke about the power of television images, the presidentialization of Canadian politics, the concentration of media ownership, the failure of leaders to address policies in a serious way during elections, the sheer nastiness and negativity of political attacks, the power of the media to set the agenda and frame issues during elections, and the need for politicians to fit into those very media frames if they wished to be covered at all.None of these concerns have vanished with time.If anything, they have hardened into place, making them even more pervasive and intractable.Yet even as so much has remained the same, so much has changed.When the conference "How Canadians Communicate Politically: The Next Generation" was convened in Calgary and Banff in late October 2009, the media and political terrains had been dramatically transformed.The revolution in web-based technology that had begun in the mid-1990s had hit the country with devastating force.As online media depleted the newspaper industry, TV networks, and local radio stations of a sizable portion of their audiences and advertising, the old lions of the traditional media lost some of their bite.The stark reality today is that every medium is merging with Canada as a distant and, to some degree, foreign land that is barely recognizable and, for the most part, irrelevant to their lives.How to draw digital natives more fully into the Canadian political spectacle remains one of the country's great challenges.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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