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Record W2335007453 · doi:10.7227/jace.17.2.4

<i>You've Got the Power</i> : Documentary Film as a Tool of Environmental Adult Education

2011· article· en· W2335007453 on OpenAlexaffabout
Darlene E. Clover

Bibliographic record

VenueJournal of Adult and Continuing Education · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsEnvironmentalismEnvironmental educationNarrativeSociologyCitizenshipPower (physics)PoliticsEnvironmental ethicsCitizenship educationAestheticsMedia studiesPedagogyPolitical scienceLawArtLiterature

Abstract

fetched live from OpenAlex

Educators call for more creative means to combat the moribund narratives of contemporary environmentalism. Using visual methodology and environmental adult education theory, this article discusses how a documentary film titled You've Got the Power works to pose questions about complex environmental issues and develop critical thinking and cultural understandings. By juxtaposing narratives and images the film artfully, critically, and emotively exposes diverse ways of knowing and viewing the world, problematises concepts of citizenship and ecological justice and illuminates the complex contemporary politics of environmentalism. Perhaps most importantly, it challenges stereotypic notions of aboriginal peoples in Canada, by highlighting their critical environmental roles and actions and thereby provides a much needed source of inspiration and hope for change.

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)0.003
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: none
Teacher disagreement score0.025
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0060.007
Scholarly communication0.0060.003
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.071
GPT teacher head0.458
Teacher spread0.387 · 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

Citations6
Published2011
Admission routes2
Has abstractyes

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