Bibliographic record
Abstract
This paper is an ethnographic study of digital culture and Iranian online political humor: a hybridized genre of folklore which converges in both online and oral spheres where it is created and shared. It specifically explores the emergence and growth of politicized humorous cellphonelore, which I term “electionlore”, during and after the 2016 February elections in Iran. Analysing different joke sub-cycles in this electionlore, I argue that they serve as a powerful tool for my informants to construct their own “newslore” (Frank 2011) and make manifest what I define as “vernacular politics” through which they become mobilized and unified in their political activism. I diverge from the theory of “resistance jokes” (Powell and Paton 1988; Bryant 2006; Davies 2011) and propose a new framework for studying political jokes in countries suspended between democracy and dictatorship, demonstrating how jokes serve as an effective and strategic form of reform and unquiet protest.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".