Opposition to political correctness as metadiscourse. Mapping the topos of the “free speech crisis” in Western right-wing discourse
Bibliographic record
Abstract
The concept of “Political correctness” (abbreviated PC) has become in the last two decades a salient features in contemporary (meta)discourses on the evolution of Western culture and language. Even though the term has now thoroughly infused our cultural and political lexicon, it remains a floating signifier which is hard to define and which conceptual borders are in constant flux. Acting as a symbolic glue, opposition to political correctness emerged as a general framework for engaging critically with some of the fundamental issues of post-materialist modernity: multiculturalism, racial inequality, sexual citizenship or education. The debate about PC is located within – and possibly at the very heart of – the shift to “cultural politics”, the politics of recognition, of identity and difference. It is important to grasp both PC and its critique as part and parcel of the much broader societal tectonic shift enacted by post-materialism. Using a Discourse-Historical Approach (DHA), the paper investigates the historical background of the emergence of the anti-PC discourse, as a backlash against the mainstreaming on US campuses of gender- and race-critical theories rooted in French (post)structuralism. It then focuses on a contemporary example of such discourse, analyzing a series of YouTube videos by the conservative Canadian academic and subsequent bestselling author Jordan Peterson. The case study highlights the manner in which anti-PC discourse capitalizes on liberal themes such as freedom of speech to articulate an anti-modern and anti-establishment critique.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.012 | 0.062 |
| Scholarly communication | 0.020 | 0.012 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".