The Media Economics and Cultural Politics of Al Jazeera English in the United States.
Bibliographic record
Abstract
Since its foundation in 2006, Al Jazeera English (AJE) grew into a leading global news outlet, yet it struggled to gain an audience and wide distribution in the United States. AJE’s availability on American cable and satellite television is miniscule compared with similar countries, Canada, the United Kingdom and Australia. In seeking to understand this puzzle, this dissertation, a case study of AJE’s circulation and audience-seeking in the United States, informs debate about globalization’s promise of larger changes in the historically one-way directionality of global news and information flow. While greater global trade and a flourishing of technologies – from satellites to the Internet – enhance the movement of media content between borders, AJE’s entry to the US market is sapped by both the domestic politics of American-Arab relations post-9/11 and a deep lack of interest in international news and affairs among Americans. This calls into question the health of the American public sphere as a “marketplace of ideas” and limits the healthy cross-cultural and transnational news and information exchange promised by both the Information Age and AJE’s mission. By claiming to devote more coverage to the “global south” and the world’s “voiceless” peoples and regions, AJE represents the prospects of a historic shift in transnational news flow imbalances, which traditionally centered news organizations in western, advanced, industrialized countries. This idea has motivated much of the popular discourse and scholarship about Al Jazeera English. Some posit that AJE can challenge the grip of world powers on news and information, promising a counter-hegemonic potential. Others suggest it expedites inter-cultural understanding as a conciliatory medium. Before scholarship can consider the implications of AJE’s brand of reporting on world affairs, it is necessary to map the actuality of AJE’s circulation. This study considers where AJE has and has not gained TV distribution in the United States and offers an explanation based on an original framework containing four main factors: political culture, media economics, the larger political context and AJE’s agency as a market entrant. These are examined and weighed using diverse research methods: content analysis, interviews, discourse analysis and an online experiment.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".