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Record W4313259509 · doi:10.34309/jp.v27i3.741

Inisiatif Perempuan Membentuk Environmental Culture sebagai Upaya Mengatasi Perubahan Iklim

2022· article· en· W4313259509 on OpenAlexaff
Ikhaputri Widiantini, Abby Gina Boang Manalu

Bibliographic record

VenueJurnal Perempuan · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicWaste Management and Recycling
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsSolidarityEnvironmental ethicsEcological crisisPerspective (graphical)SociologyPolitical scienceLawPoliticsPhilosophy

Abstract

fetched live from OpenAlex

This research discusses the efforts of women in the community as a form of environmental culture in responding to the climate change crisis. The arrogance issue of patriarchal reason has distorted human ability to recognize the main problem of environmental damage. Humans are trapped in the illusion of the domination of reason which seeks to control nature as non-humans. As a result of this arrogance of reason, culture is formed hierarchically dominating nature (non-humans). We offer a change in cultural perspective through the environmental culture raised by Val Plumwood. This culture with an ecological and caring perspective is a form of the feminist ecological thought movement. We use the method of analyzing feminist issues through feminist knowledge standpoints that interact with ecological research methods. We collect data through various media with a focus on telling the experiences of women in dealing with environmental problems. Our analysis comes to the conclusion that concrete initiatives and actions are needed that involve all ecological elements as a form of solidarity. In this way, we no longer glorify humans as the rulers of reason, but rather create critical and creative communities in realizing an environmental culture.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0100.001

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 head0.007
GPT teacher head0.201
Teacher spread0.193 · 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

Citations3
Published2022
Admission routes1
Has abstractyes

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