Mythes modernes, propagande et communications publicitaires de l’armée canadienne en 2010
Bibliographic record
Abstract
L’auteure appréhende la communication gouvernementale canadienne à la lumière des apports théoriques de Jacques Ellul sur les mythes modernes du 20e siècle et sur la propagande. Il ressort de l’analyse des propos des sujets parlants et des images de 26 vidéos diffusées sur le site Internet de l’armée canadienne, destinées au recrutement de jeunes de 18 à 34 ans (2010), une typologie de mythes fondateurs (Science, Histoire, Progrès) et de mythes secondaires connexes (progrès technique, technicien performant, formation et carrière idéales, réalisation du bonheur matériel, fratrie, valeurs supérieures, héros exemplaire, vie rêvée, jeunesse promise à des lendemains qui chantent). Ces mythes supportent l’idée que le métier des armes est un métier comme un autre tout en occultant sa finalité guerrière et létale. Constitutifs de communications publicitaires largement financées et diffusées par le gouvernement conservateur de Steven Harper, via le ministère de la Défense nationale, en poussant les jeunes Canadiens à s’engager dans l’armée, ces mythes qui assurent l’efficacité orthopraxique de ces communications, apparentent ces dernières à de la propagande.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.011 | 0.011 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.022 | 0.002 |
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".