The Press of Quebec Through Media Regionalism Prism: From Origin to Digital Epoch (XVIII – the beginning of the XXI century)
Bibliographic record
Abstract
Today all national languages and cultures feel this inconceivable pressing by global English-Language digital world transformation. In addition, we examine second actual problem – information inequality in multinational countries and “answer-reaction” of one national minority. Quebec is the only French-speaking province of Canada. We present agenda of Quebec French-language press during two centuries through Media Regionalism – our specific term for reaction of Quebec Francophones constantly surrounded by total English-speaking information environment. Practically, media regionalism is not studied by Russian researchers. Analyzing Quebec French-language press as material we formulate hypothesis of research: media regionalism is its historical feature, which defends successfully cultural and traditional values of Quebec. Key aspect of the present research problem is scientific definition for media regionalism. For characterization of media regionalism evolution in Quebec we used mainly the methodology of complex analysis. As a result, we should note that media regionalism, on the one hand, defends Quebec identity, but on the other hand, reminds self-censorship of newspapers. Elucidating the questions of French language, Quebec traditions and culture, media regionalism refuses international news, information of other Canadian provinces, etc. Seeing media regionalism as the basis of Quebec information politics during more than two centuries, we can predicate its future great vitality for French-language press. Quebec media regionalism is peculiar defense from external destructive factors – such as transition to British Crown in the XVIIIth century or global digital world transformation in the XXIth. Media regionalism information problem is important for many other multinational countries. Finally, it is necessary to continue these studies.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 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".