Sectoral Labour Flows and Agricultural Wages in India, 1983-2004: Has Growth Trickled Down?
Bibliographic record
Abstract
We would like to thank Paul Beaudry, Andrew Foster, Shubashis Gangopadhyay, Peter Lanjouw, Dilip Mookherjee, Suresh Tendulkar, Alessandro Tarrozi, the participants of the World Bank workshop on Equity and Development (7-8 December 2004) and the participants of the “Workshop on the Indian Economy: Policy and Performance 1980-2000” held at the Centre for India and South Asia Research, University of British Columbia in Vancouver (in June 2005) for their helpful comments. We are grateful to the Shastri Indo-Canadian Institute for financial support through the SHARP programme and to India Development Foundation, Gurgaon, for their hospitality and generous support.Mukesh Eswaran (
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".