A critical analysis of media discourse on information technology: preliminary results of a proposed method for critical discourse analysis
Bibliographic record
Abstract
Abstract Since the 1980s, there has been a growing body of critical theory in information systems research. A central theoretical foundation of this research is Habermas’ theory of communicative action, which focuses on implications of speech and proposes general normative standards for communication. Habermas also places particular emphasis on the importance of the public sphere in a democratic society, critiquing the role of the media and other actors in shaping public discourse. While there has been growing emphasis on critical discourse analysis (CDA), there has been limited effort to systematically apply Habermas’ validity claims to empirical research. Moreover, while critical research in information systems has examined communication within the organizational context, public discourse on information technology has received little attention. The paper makes three primary contributions: (1) it responds to Habermas’ call for empirical research to ground and extend his theory of communication in every day critical practice; (2) it proposes an approach to applying Habermas’ theory of communication to CDA; and (3) it extends the reach of critical research in information systems beyond micro‐level organizational concerns and opens up to critical reflection and debate on the impact of systematically distorted communication about technology in the public sphere.
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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 | 0.032 | 0.076 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".