Analyse de l’image politique de François Legault sur Instagram pendant la crise de la COVID-19
Bibliographic record
Abstract
Background: This article addresses communications on Instagram by Québec Premier François Legault. We were particularly interested in his use of this platform to manage the COVID-19 crisis. For this article, we carried out a content, discourse, and visual analysis of the publications on the Instagram account of the Premier of Québec during two key periods, the beginning of the COVID-19 crisis from March 12 to April 13, 2020, and its continuation from January 6 to February 8, 2021. Analysis: We draw on a content, discourse, and visual analysis of the Premier’s messages on the Instagram platform to understand the strategies used by the Québec government on the Premier’s Instagram feed during the COVID-19 crisis. Conclusions and implications: Through this study, we show the uses of Instagram and how this platform was leveraged to communicate during the COVID-19 pandemic. Legault responded to the urgency of crisis management by showing strong leadership and staying on message.
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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 | 0.008 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".