Multi-platform production: full speed ahead. The case of the Canadian company Québecor, 1995–2010
Bibliographic record
Abstract
This paper analyzes the strategies of the Canadian corporation Quebecor, a conglomerate regarded as the prototypical media company and a veteran in the process of gradual media convergence. This case study is based on ethnographic fieldwork conducted between 1999 and 2005, and on a review of the corporation’s activities five years later, in 2010. Synergistically integrating cross–promoting media, strategic partnerships with other media, and structural innovation, Quebecor is the most strongly committed actor in multiplatform production in Quebec – and beyond in English Canada. It has also become an increasingly avid proponent of the concept of the multitasking journalist. The analysis proposed here illustrates not only the transformation of the work of Quebecor employees but also the strategies deployed by a conglomerate to control financial and business opportunities anticipated through media convergence.
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How this classification was reachedexpand
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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".