A computer-aided investigation of cultural representations in media discourse /
Bibliographic record
Abstract
The aim of this study was to explore cultural representations conveyed in the media discourse using a content-analysis software called ALCESTE. Our exploration focused on a sample of written media discourse in the Quebecois linguistic context, the Michaud affair, comparing and contrasting two different perspectives. We retrieved from the Internet all the articles published between December 2000 and January 2001 related to the case under study from two English Canadian newspapers, the National Post and The Gazette . The two corpora were submitted to ALCESTE software. Using the factorial correspondence analysis of ALCESTE, we identified four different lexical worlds in the corpora of over fifty thousand words. Those lexical worlds correspond to the different positions of the utterers vis-a-vis the issue under study. Specific vocabulary from the lexical worlds were found to convey cultural representations. Our study has permitted to uncover differences and similarities in the analysis of the Michaud affair reported in the National Post , an English newspaper in Toronto, Ontario, and in The Gazette , an English newspaper edited in Montreal, Quebec.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".