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Record W2120800896 · doi:10.25009/cpue.v0i21.1713

La ética ambiental como proyecto de vida y “obra” social: Un desafío de formación

2015· article· es· W2120800896 on OpenAlexaff
Lucie Sauvé, Carine Villemagne

Bibliographic record

VenueCPU-e Revista de Investigación Educativa · 2015
Typearticle
Languagees
FieldEnvironmental Science
TopicEnvironmental Philosophy and Ethics
Canadian institutionsUniversité du Québec
Fundersnot available
KeywordsHumanitiesHuman beingSociologyPhilosophy

Abstract

fetched live from OpenAlex

En este artículo se exponen y analizan las principales corrientes en el campo de la ética ambiental. Mediante un análisis comparativo de once corrientes y el encuadre de sus aportaciones en relación a tres ejes que enmarcan la discusión de los conceptos de valor, ética y moral –el ser humano, la vida y los sistemas de vida o ecosistemas–, descubrimos la necesidad de una discusión académica sobre los valores ambientales, la cual ayuda a desarrollar procesos de formación y proyectos de educación ambiental pertinentes. Por tanto, reconocer la pluralidad de diferentes posturas pero también la factibilidad y necesidad de desarrollar enfoques pedagógicos que despierten una mayor sensibilidad, compromiso y responsabilidad desde las propias elecciones éticas de los seres humanos, permitirá generar éticas que, si bien son antropogénicas, no sean antropocéntricas.AbstractThis essay explains and analyzes the main currents in the field of environmental ethics. By means of a comparative analysis of eleven ethical stances and the explanation of theirs contributions regarding to three different axis –human being, life and life systems or ecosystems– that orient the discussion about the concepts of value, ethics and moral, we discover the need of an academic discussion about environmental values. These values help us to develop relevant formative processes and environmental education projects. Therefore, examining the plurality of different stances as well as the need of developing pedagogic approaches that stimulate more sensitivity, commitment and responsibility from the own ethical elections of human beings, it’s possible to develop non anthropocentric –although anthropogenic– ethics.Recibido: 15 de enero de 2015Aceptado: 22 de mayo de 2015

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.418
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.004
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.002

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 head0.042
GPT teacher head0.304
Teacher spread0.262 · 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.

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

Citations14
Published2015
Admission routes1
Has abstractyes

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