Eating words: a discourse historical analysis of the public debate over India’s 2013 National Food Security Act
Bibliographic record
Abstract
Purpose – This paper aims to provide a situated critical discourse analysis of the public debate around India’s 2013 National Food Security Act (NFSA), describing its rhetorical characteristics and the context within which it has taken place. Design/methodology/approach – Using Wodak’s (2001) Discourse Historical Approach (DHA), the authors examine media coverage of the NFSA, attending to perspectivization, intensification and mitigation and representational and argumentational strategies. The authors also consider this coverage in light of its intratextual, intertextual, situational and wider socio-political and economic contexts. The corpus consists of 29 English-language Indian newspaper and magazine articles, published in print and online between 2011 and 2014. Findings – This paper explains the rhetorical purchase of the term “food security” in contemporary Indian public policy debates by comparing the leftist, right wing and centrist arguments. Research limitations/implications – Owing to the detailed qualitative analysis presented here, the corpus is necessarily limited in size. Newspaper articles contributed by one of the authors were omitted from the study. Originality/value – The DHA claims to be an interdisciplinary framework, but relatively few studies involve true cross-disciplinary research. By contrast, this study relies on close collaboration by scholars active in economics and applied linguistics – thus, demonstrating both the potential for, and the value of, working coherently across academic disciplines. Also, unlike most DHA studies, which interrogate dominant discourses, this paper compares diverse discourses competing for influence.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".