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Building capacity for environmental engagement and leadership: An ecosocial work perspective

2011· article· en· W2122886238 on OpenAlexaff
Mishka Lysack

Bibliographic record

VenueInternational Journal of Social Welfare · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicReligion, Ecology, and Ethics
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsFaithPerspective (graphical)Capacity buildingSpiritualitySociologyContext (archaeology)Public relationsEnvironmental ethicsPolitical scienceEnvironmental educationPedagogyGeographyMedicine

Abstract

fetched live from OpenAlex

Lysack M. Building capacity for environmental engagement and leadership: an ecosocial work perspective In the context of accelerating environmental decline and climate change, this article explores the opportunities for building capacity for leadership within the faith communities to advocate for the protection of the climate and environment. The author discusses the tools for building capacity through faith‐based environmental education to equip members of faith communities to move from being passive consumers to active environmental citizens. The ways in which ecosocial workers, particularly those interested in religion and spirituality, could play a role in facilitating the emergence of leadership capacity within faith communities to care and advocate for the earth are also examined. The article highlights the theoretical resources and practices of community engagement and public education that ecosocial workers could contribute to this project of building a broad ethically centred environmental movement.

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)0.008
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0080.038
Scholarly communication0.0090.008
Open science0.0010.011
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0040.000

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 head0.193
GPT teacher head0.360
Teacher spread0.167 · 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 designTheoretical or conceptual
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

Citations26
Published2011
Admission routes1
Has abstractyes

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