Invisible Media Labour: Participatory Moderation at Refugee Radio Stations in Germany
Bibliographic record
Abstract
This dissertation explores the role of media structures in serving the public sphere. I argue for the concept of participatory moderation (PM) which refers to the labour of media professionals in engaging their audiences to prepare for deliberation on community issues. This includes activities such as organizing, coordinating, facilitating, educating, translating, interpreting federal and local policies, establishing connections within civil society organizations, and building networks that are not typically considered part of media jobs. Using a multi-sited ethnography approach, this study examines the presence of PM in the practices of three refugee radio programs established at community radio stations in Germany, operating in three federal states: Hamburg, Sachsen-Anhalt, and Baden-Württemberg. The study focuses on the use of these media structures by refugees during the post-refugee crisis period, from 2020 to 2023, to ensure their participation in the public sphere and larger conversations related to their problems. It reveals the challenges and inequalities that radio workers encounter in gaining access to the public sphere, leading to additional work to ensure community participation in the public sphere through these media projects. I argue that the efforts of staff media workers and volunteers, which the conceptual framework I develop in this dissertation interprets as activities related to participatory moderation, should be recognized as one of the ‘norms’ for media institutions serving the public sphere in the theories of the public sphere. Acknowledging and appreciating this labour should help challenge the conventional vision of the roles of media structures in deliberative processes. Key words: media and public sphere, deliberation, community radio, refugees, multi-sited ethnography, participatory moderation.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.011 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| 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".