Bibliographic record
Abstract
Focusing on the failed coup attempt organized by a faction within the Turkish Armed Forces on July 15, 2016, this paper examines the soundscape of Islamic populism (Hadiz, 2016) as embraced by Turkey’s ruling Justice and Development Party (AKP) and its affective-auditory publics. Drawing on Althusser’s theories of ideology and interpellation concerning the Islamic call (Spadola, 2014), I explore AKP’s strategic use of Islamic sound as affect in governmentalizing urban space in order to understand the role that sound played in galvanizing support against the attempted coup. During the first twenty-four hours of the coup attempt, systematically regenerating discursive modes of Islamic rhetoric and sounds, utilizing the narratives of democracy, nationalism, and treachery to mobilize its publics, AKP re-cultivated the already existing polarized identity politics and recreated the sectarian spaces of belonging and otherness. I argue that AKP’s appropriation of sonic and aural qualities of Islam – particularly the public recitation of Sala (a form of Islamic call) – purposefully rechannelled the “ethical listening” (Hirschkind, 2006) of pious selves into a politically (re)functionalized listening in the populist reproduction of an Islamic soundscape. Such reproduction of the urban soundscape was responded to in a variety of ways by the mobilized auditory publics in service of the party while creating silenced private spaces of opposition. NB: The article contains sound examples. In order to listen to embedded audio files, you must first download the pdf file and then open it with Adobe Acrobat.
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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 | 0.001 | 0.002 |
| 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 | 0.012 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".