Bibliographic record
Abstract
My guest today Somini Sengupta is the United Nations correspondent for the New York Times. She's the author of the new book The End of Karma: Hope and Fury Among India's Young which tells the story of a huge demographic challenge facing India today, where 365 million people are between the ages of 10 and 24. It is the youngest country on the planet, and through storytelling and reporting, Somini puts the experiences of India's young into the broader context of the country's political, social and economic challenges. Somini was born in Calcutta, but came to the Canada and then the USA at a young age. She joined the New York Times in the mid 1990s and she tells some powerful stories from her reporting in Africa in the early 2000s, including Liberia, Congo and Darfur. We kick off discussing her new book, and a term she coined to describe India's youth generation, the \\"noonday children.\\"
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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) | 0.001 | 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) | 0.817 | 0.056 |
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".