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Record W2766280128

Global to Village| Toward Multiple Conceptions of Human-Nature Relationship: The “Human-Nature Unity” Frame Found in a Chinese Village

2017· article· en· W2766280128 on OpenAlexaff
Sibo Chen

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicChinese history and philosophy
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsSociologyHumanityFrame (networking)ChinaSpectacleGlobalizationEnvironmental ethicsConsumption (sociology)EpistemologyAestheticsSocial sciencePolitical scienceLawPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

Entangled within dominant Western ecocultural conceptions, “spectacular nature” is a commonsense frame that perceives nature as a scenic and resourceful spectacle alienated from humanity. By analyzing the human–nature relationship implied by this frame, this article seeks to reveal its inadequacy in accounting for the diversified conceptions of nature held by traditional knowledge systems across the world. To further ground this theoretical critique, the article also examines how residents in a small Chinese village called Heyang make sense of their surrounding environment. The Heyang case suggests that, although China’s rapid urbanization and integration into neoliberal globalization has made more and more people there consider nature as an alienated spectacle for consumption, indigenous culture remains influential in mediating Chinese people’s conceptual engagement with nature, especially in many rural areas where daily lives are still primarily organized around agricultural activities. The article ends by proposing a theoretical move toward multiple conceptions of a human–nature relationship, which begins with acknowledging diverse experiences of the world.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.019
Scholarly communication0.0030.003
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.257
GPT teacher head0.583
Teacher spread0.326 · 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
Published2017
Admission routes1
Has abstractyes

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