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Record W2326057425 · doi:10.1177/0169796x12470553

Traditional Veterinary in Rural Tamil Nadu

2013· article· en· W2326057425 on OpenAlexaff
Maria Costanza Torri

Bibliographic record

VenueJournal of Developing Societies · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEthnobotanical and Medicinal Plants Studies
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsTamilLivelihoodSocioeconomic statusSocioeconomicsLivestockRural areaGeographyPopulationTraditional medicineAgricultureVeterinary medicineMedicineEnvironmental healthSociology

Abstract

fetched live from OpenAlex

Nearly two-thirds of the world’s rural poor depend on livestock as a critical component of their livelihood. Modern ethnoveterinary health delivery is not easily accessible for the rural population, who still depends on traditional medicinal practices. India has rich ethnoveterinary health traditions. Nevertheless, these practices are facing the threat of rapid erosion. The vast majority of the medicinal plants used in veterinary in India have been studied from a pharmacological point of view. These studies, although giving important insights into the local traditional ethnoveterinary medicine in terms of the therapeutical value of the plants, fail however to portray the socioeconomic impact of this form of medicine on local communities. This article aims to overcome this shortcoming by analyzing the socioeconomic and health values of medicinal plants among the rural communities in Tamil Nadu, India, as well as their role in human health.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.009
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.067
GPT teacher head0.245
Teacher spread0.178 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2013
Admission routes1
Has abstractyes

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