The platformization of cultural production: Theorizing the contingent cultural commodity
Bibliographic record
Abstract
This article explores how the political economy of the cultural industries changes through platformization: the penetration of economic and infrastructural extensions of online platforms into the web, affecting the production, distribution, and circulation of cultural content. It pursues this investigation in critical dialogue with current research in business studies, political economy, and software studies. Focusing on the production of news and games, the analysis shows that in economic terms platformization entails the replacement of two-sided market structures with complex multisided platform configurations, dominated by big platform corporations. Cultural content producers have to continuously grapple with seemingly serendipitous changes in platform governance, ranging from content curation to pricing strategies. Simultaneously, these producers are enticed by new platform services and infrastructural changes. In the process, cultural commodities become fundamentally “contingent,” that is increasingly modular in design and continuously reworked and repackaged, informed by datafied user feedback.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.028 |
| Scholarly communication | 0.009 | 0.017 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".