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Record W3009537804 · doi:10.25071/1916-4467.40435

Considering the Role of Documentary Media in Environmental Education

2020· article· en· W3009537804 on OpenAlexaffvenue
Claire Ahn

Bibliographic record

VenueJournal of the Canadian Association for Curriculum Studies · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change Communication and Perception
Canadian institutionsQueen's University
Fundersnot available
KeywordsRhetorical questionEnvironmental educationVariety (cybernetics)Stewardship (theology)Environmental stewardshipRhetoricPsychologyVisual rhetoricSociologyPublic relationsPedagogyPolitical scienceEnvironmental resource managementComputer scienceArtLinguistics

Abstract

fetched live from OpenAlex

Environmental issues continue to be a growing global concern. Many curricular documents have added environment-related topics into a variety of grade levels and subjects with the hope of increasing student awareness at a time when environmental stewardship is a top priority. Traditional approaches to environmental education often include engaging students with the outdoors, and while this is an integral part of developing students’ environmental awareness, much of what students learn about the environment is from the media, which includes visual imagery. As we contemplate how best to engage students in reflecting on what it means to live in a sustainable fashion, it is also important to consider the merits of visual rhetorical modes in environmental communication, such as documentary film. This paper draws upon findings from a study that explored how viewers react to particular visual imagery. The data revealed the most powerful rhetorical effect was observed when participants drew links between the visual content of the video clips and a personally significant outdoor place, demonstrating that a personal connection to place may make a direct impact on viewers’ reactions to visual rhetoric in environmental documentaries, thus possibly causing the viewer to develop a deeper awareness of the issues.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.658
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.154
GPT teacher head0.373
Teacher spread0.219 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations8
Published2020
Admission routes2
Has abstractyes

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Same venueJournal of the Canadian Association for Curriculum StudiesSame topicClimate Change Communication and PerceptionFrench-language works237,207