Making fun of the standard tongue: Enregisterment, social difference, and Kurdish language humor
Bibliographic record
Abstract
Abstract This article analyzes how humor around contrasts between standard and non‐standard Northern, i.e., Kurmanji, Kurdish spoken in Turkey contributes to the enregisterment of standard Kurdish, arguing that Kurdish language jokes promote the recognition and, to different degrees, uptake of standardized linguistic repertoires among differently situated Kurdish audiences, while also promoting alternative ideological perspectives through which the contrasts between standard and non‐standard language can be evaluated. In developing this analysis, the article also considers how Kurdish language humor functions to both reproduce widely circulating language ideologies and subvert them, inviting Kurdish audiences in contemporary Turkey and North Kurdistan to be reflexive about language and the ideological processes through which value is ascribed to it. It argues that for many Kurds in Turkey, Kurdish linguistic revival and national unity are premised less on the accomplishment of Kurdish linguistic uniformity and more on the ongoing recognition and valorization of linguistic and social differences; Kurdish standard language can function in ways that not only minimize but also draw attention to linguistic variation in socially consequential ways.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.018 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".