Reconstructing the Political Economy of Communication for the Digital Media Age
Bibliographic record
Abstract
Within communication studies, the political economy of communication (PEC) approach is typically seen to be the sole preserve of Marxist scholars, with origins in the late 20 th century. Such a view, however, obscures an older, trans-Atlantic political economy tradition forged by Europe and North American scholars who made communications media central objects of their analyses in the late-19 th and early-20 th centuries. This earlier tradition was imported into communication studies through the halfway house of sociology, mostly after the turn of the 20 th century, thereby thoroughly entangling the intellectual history of communication studies with that of political economy from the beginning. Moreover, the formative years of the field were never the barren ‘administrative wasteland’ often thought. Indeed, combined with the research done beyond the field’s borders by economists, business historians, legal and regulatory scholars, etc. throughout the 20 th Century, a wealth of underused resources is close-to-hand that can help us to reimagine and reconstruct what we mean by the PEC traditions today. This paper starts to recover these neglected elements, and the contributions of the institutionalist and Cultural Industries schools especially. It closes with a survey of recent PEC research and a handful of provocations that contemporary researchers might explore: (1) in an evermore internet- and mobile wireless-centric world, bandwidth is king, not content; (2) subscriber fees are now the economic base of the media not advertising, by roughly a 3:1 ratio; (3) rather than seeing media as a ‘unified system’, developments vary greatly across media: some are growing fast, others stagnating, and yet others appear to be in decline; (4) people create, consume and share a lot of media outside the market; and (5) contra neoliberal mythology, the role of the state remains vital: as regulator, a counter to market power, investor and in terms of surveillance.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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; both teacher heads agree on what is shown here.
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".