Bibliographic record
Abstract
This article discusses the urban housing situation in India using the data from Census and NSS Housing Condition Rounds, and it also estimates the urban housing shortages in 2012 by Caste and Ethnic groups, following the methodology of the Technical Group on Urban Housing Shortage, 2012–17 (TG-12). The TG-12 estimated the number of urban households to be 81.35 million and urban housing shortage to be 18.78 million in 2012. Households living in congested conditions were found to be one of the main factors leading to these housing shortages. Households from economically weaker sections and lower income groups accounted majorly for these shortages. Among caste and ethnic groups, housing shortages were found to be high for Scheduled Caste households than Scheduled Tribe and other households, mainly on account of congestion factor. The results suggest the need for attention towards urban housing with targeted group-specific policies (economic and social) and socio-spatial perspective to eradicate shelter deprivation and to enhance the quality of life of the people in urban India.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".