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Record W4403534953 · doi:10.5751/es-15585-290409

Caring for standing crops in the Himalayas: embedded notion of saving to save

2024· article· en· W4403534953 on OpenAlexvenueno aff
Jiban Mani Poudel

Bibliographic record

VenueEcology and Society · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural risk and resilience
Canadian institutionsnot available
Fundersnot available
KeywordsAgroforestryBusinessNatural resource economicsEnvironmental resource managementEconomicsEnvironmental science

Abstract

fetched live from OpenAlex

In the Himalayas, human beings have developed several behaviors and practices in the process of adaptation to the harsh environment. The theme of the paper is to explore the notion of care through the local practices of caring for standing crops. The paper is based on the more than nine-month-long ethnographic study in the Nhāson Valley of Nepal. The findings reveal that caring for standing crops is not just rooted in technical rationality imposed by external agencies; it is cultivated in the concept of ethics of saving to save and respect for others’ property. The beliefs and practices of caring for standing crops reveal that the landscape is not only for humans and animals but also for divine beings, whose presence must be recognized and acknowledged when discussing human-nature relationships. The study challenges the reductionist approach of these relationships by focusing on how farmers’ workaday practices like fencing; implementing social regulations; and performing rituals bring science and society together. This integration creates a resilient and robust ecological framework for environmental study.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.021
Scholarly communication0.0040.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.252
Teacher spread0.236 · 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 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

Citations1
Published2024
Admission routes1
Has abstractyes

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