Discursivity, difference, and disruption
Bibliographic record
Abstract
We offer a genealogical perspective on the reflexive critique that consumer culture theory (CCT) has institutionalized a hyperindividualizing, overly agentic, and sociologically impoverished mode of analysis that impedes systematic investigations into the historical, ideological, and sociological shaping of marketing, markets, and consumption systems. Our analysis shows that the CCT pioneers embraced the humanistic/experientialist discourse to carve out a disciplinary niche in a largely antagonistic marketing field. However, this original epistemological orientation has long given way to a multilayered CCT heteroglossia that features a broad range of theorizations integrating structural and agentic levels of analysis. We close with a discussion of how reflexive debates over CCT's supposed biases toward the agentic reproduce symbolic distinctions between North American and European scholarship styles and thus primarily reflect the institutional interests of those positioned in the Northern hemisphere. By destabilizing the north–south and center–periphery relations of power that have long-framed metropole social science constructions of the marginalized cultural “other” as an object of study—rather than as a producer of legitimate knowledge and theory—the CCT heteroglossia can be further diversified and enriched through a blending of historical, material, critical, and experiential perspectives.
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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 | 0.009 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.006 | 0.073 |
| Scholarly communication | 0.013 | 0.010 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".