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Record W2590619941 · doi:10.25336/p62c8f

The persistent caste divide in India’s infant mortality: A study of Dalits (ex-untouchables), Adivasis (indigenous peoples), Other Backward Classes, and forward castes

2017· article· en· W2590619941 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCanadian Studies in Population · 2017
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsCarleton University
Fundersnot available
KeywordsCasteSocioeconomic statusIndigenousDemographyGeographyEthnologyHumanitiesSocioeconomicsSociologyPolitical sciencePopulationArtBiology

Abstract

fetched live from OpenAlex

Using data from two national surveys, this paper examines caste differences in infant mortality in India. We find that children from the three lower caste groups—Dalits (ex-untouchables), Adivasis (indigenous peoples), and Other Backward Classes—are significantly more likely than forward-caste children to die young. While this observation largely mirrors caste differences in socioeconomic conditions, low socioeconomic status is found to be only a partial explanation for higher infant mortality among lower castes. Higher mortality risks among backward-class children are almost entirely attributable to background characteristics. However, Dalit children are most vulnerable in the neonatal period even when all background characteristics are taken into account, whereas Adivasi children remain highly vulnerable in the post-neonatal period.Au moyen des données provenant des deux enquêtes nationales, cet article examine les différences dans la mortalité infantile par caste en Inde. Nous constatons que, par rapport aux enfants des castes élevées, ceux des trois castes inférieures, notamment les dalits (les ex-intouchables), les adivasis (peuples indigènes) et autres classes défavorisées (plusieurs castes désignées comme appartenant à un groupe défavorisé) courent un risque beaucoup plus grand de mourir jeunes. Bien que cette observation reflète largement les différences entre les castes sur le plan socioéconomique, le faible niveau socioéconomique n’explique qu’en partie le taux de mortalité plus élevé chez les castes inférieures. Les risques de mortalité des enfants des castes inférieures étaient presque entièrement attribuables aux caractéristiques des antécédents de la mère. Cependant, les enfants dalits demeurent les plus vulnérables pendant la période néonatale, bien que le risque de mortalité demeure le même que celui des enfants des castes supérieures pour la période post-néonatale. L’inverse est vrai pour les enfants adivasis : les caractéristiques des antécédents expliquent leur plus grande vulnérabilité pendant la période néonatale, mais pas pendant la période post-néonatale.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.267
Threshold uncertainty score0.496

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.056
GPT teacher head0.347
Teacher spread0.291 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it