Subtle Curry Traits: exploring constructions of “South Asianness” in a meme-sharing group
Bibliographic record
Abstract
Subtle Curry Traits (SCT) is a digital group, comprising of almost 1 million members, that was created by diasporic South Asian youth to share humorous posts. While the group serves as an avenue for community building, it constructs a South Asian cultural identity that is based on inclusion and exclusion. Informed by critical cultural studies, post-colonial scholars and, anti-racist transnational feminists I analyze how notions of South Asianness are articulated, expressed, and constructed in the group, paying particular attention to the identities that are erased and overlooked. I do this by providing a narrative literature review of digital spaces and diasporic youth, historical and diasporic formations of South Asianness, and by conducting a multimodal critical discourse analysis on 76 posts shared on SCT’s Instagram page. I find that the traits and realities highlighted on the group as “South Asian” construct a heteropatriarchal, casteist, and North-Indian based identity as South Asian.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.017 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| 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".