Daily Wires and Daily Blossoms: Cultivating Regimes of Circulation in Tamil India's Newspaper Revolution
Bibliographic record
Abstract
Two of Tamil India's most popular newspapers both claim to be using “spoken” as opposed to “written” varieties of Tamil, despite appealing to different class and gender sensibilities. Developing a method that can take into account the relations among (1) explicit metadiscourses on journalistic language, (2) variegated reading practices, and (3) the formal qualities of newspapers as text artifacts, I argue that what is at stake in the difference between the two papers in my comparison is in fact a difference inregimes of circulation—cultivated habits of animating artifactually mediated texts, enabling the movement of discourse along predictable social trajectories. Claims to using the language of speech in the press refer to two very different phenomena: a Tamil written to be spoken aloud at the point of reading in one paper, and a “spoken Tamil” made to be read silently in the other.[media, publics, reading, textuality, circulation, India]
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.012 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".