Appraisal and Party Positioning in Parliamentary Debates: A Usage-Based Critical Discourse Analysis
Bibliographic record
Abstract
This article presents a corpus-driven study of evaluative discourses surrounding asylum seekers in parliamentary debates. It explores how Australian political parties have expressed unfavorable attitudes toward asylum seekers. These attitudes are operationalized by implementing Martin and White’s appraisal framework, which comprises affectual (affect), ethical (judgment), and aesthetic (appreciation) values. The findings reveal that the subcategories of affect, judgment, and appreciation are strategically deployed by both right- and left-wing parties. The right-wing discourse, conveying ethical values, emphasizes the difference between “in” and “out” groups, whereas the left-wing discourse, engaged in affectual values, demonstrates their humanitarian side. The study has also a methodological focus, namely, testing the feasibility of the behavioral profile approach in critical discourse analysis to obtain more replicable and reliable quantitative results. The method consists of the manual annotation of the corpus and multivariate statistical analysis.
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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 | 0.016 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.011 | 0.008 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".