Demystifying the Myth of Genderlect through Intertextuality in Global Media Discourse
Bibliographic record
Abstract
This article outlines a gender-based analysis at the connection of critical discourse analysis and intertextuality, with the aim of providing a rich analyses of the multifaceted mechanisms of power and ideology in discourse in supporting hierarchically gendered social orders. The focus of this research is to identify how gender is socially constructed through linguistic choices (especially intertextuality) and discursive practices in media discourse and how these discursive practices in media discourse contribute to create a feminist perspective. The present article has collected 60 talk shows, panel discussions and interviews from 5 global news channels. A corpus is built and a linguistic analysis is conducted where Faircloughs Intertextuality is used as research Methodology. Moreover, Van Dijks socio-cognitive model is used as research framework in which data is analysed on us versus them dichotomy and at micro and macro level of discourse. It is observed that through the use of intertextuality, dominant ideology is (re)- created in feminist media discourse.
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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 | 0.013 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.005 | 0.052 |
| Scholarly communication | 0.014 | 0.017 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| 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 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".