Bibliographic record
Abstract
HYDERABADIS1 people from the city of Hyderabad or the former\nstate of Hyderabad, have been migrating abroad in some\nnumbers since the late 1940s and especially since the late\n1960s. They have gone to work or live in rather diverse places,\nmost notably Pakistan, the UK, Australia, the US, Canada, and\nthe Gulf states of the Middle East. Most among them have\ntried to maintain some degree of Hyderabadi identity. They\nretain connections to their homeland, build networks across\nnational boundaries, and try to teach their children about\nHyderabadi culture. They and their children have also become\nparticipants to varying degrees in the national life of the nation-\nstates to which they have migrated. The specific environments\nin the destination countries, particularly the legal and\npolitical conditions governing migration, working conditions,\nand citizenship, provide both constraints and opportunities for\nthe immigrants as they selectively shape new identities. For .the\ntime being, we must assume some initial identity or identities\nrelating them to their homeland, locating them within it but\nbeing carried abroad and worked within the new locations.\n"Hyderabadi", or "a person from Hyderabad", was an identity\nthat linked one closely to a state.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.005 |
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; both teacher heads agree on what is shown here.
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".