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Record W4400335174 · doi:10.4103/ijcm.ijcm_206_22

Farmers’ Suicides in India: A Qualitative Study of Andhra Pradesh (AP) and Telangana States of India

2024· article· en· W4400335174 on OpenAlexaboutno aff
Laila Memdani, Azim Memdani, Anisha Memdani

Bibliographic record

VenueIndian Journal of Community Medicine · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural risk and resilience
Canadian institutionsnot available
Fundersnot available
KeywordsAgricultureSocioeconomicsQuarter (Canadian coin)GeographyNatural disasterQualitative researchEnvironmental healthMedicineSocial scienceSociology

Abstract

fetched live from OpenAlex

Suicides by the farmers' is increasing in India. From 2005 to 2020, 319,598 famers committed suicide and in states of AP and Telangana this number was 319,598 which is 28% of the total. It implies that more than one quarter of the total number of farmers' who committed suicide in the ountry were from Telangana and AP. Worldwide farming is considered as a high risk occupation for mental diseases. May be because of the nature of farming and the risk of natural calamities. The study aims to identify the factors that contribute to farmer suicides in Telangana andAndhra Pradesh (AP) and to propose preventive solutions for the problem. In this research in-depth interviews were done with the close relatives ofthe person who committed suicide and qualitative methodology is used. We find that the main causes of farmers suicides are economic and not themental health of the farmers.

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.

How this classification was reachedexpand

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)0.002
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.390
Threshold uncertainty score0.362

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.032
GPT teacher head0.327
Teacher spread0.294 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2024
Admission routes1
Has abstractyes

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