Oligopolies of the past? Habermas, Bourdieu, and conceptual approaches to news agencies
Bibliographic record
Abstract
This article uses the history of news agencies, particularly in Germany, to explore key theories about media transitions. First, many over-emphasize technology as an autonomous factor divorced from politics, economics, and culture. Historical methodologies remind us that technology is socially constructed, as I show using the example of wireless technology. Second, the economic dominance of platforms has become central to the debate about how to reform the Internet. This too draws on long-standing conceptual approaches to media, pioneered by Habermas. Like online platforms, news agencies were bottlenecks for news; their history reminds us that their dominance stemmed from politics as much as economics. Finally, I suggest that we need to include Bourdieu’s ideas of symbolic power and institutions to understand why certain media firms became so central. To understand news agencies, we can thus combine the work of Habermas and Bourdieu with theories about the social construction of technology to retrace the interaction between politics, economics, technology, and social norms that imbued news agencies with such power for so long.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.007 | 0.033 |
| Scholarly communication | 0.015 | 0.017 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".