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Record W6907839267 · doi:10.25316/ir-17660

Lived experiences and emergent practices : eight conversations with Metro Vancouver urban environmental educators

2022· other· en· W6907839267 on OpenAlexaboutno aff

Bibliographic record

VenueVIURRSpace (Vancouver Island University) · 2022
Typeother
Languageen
FieldEnvironmental Science
TopicEnvironmental Education and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsSustainabilityPhenomenology (philosophy)Lived experienceParticipant observationEnvironmental educationUrban planningUrban sustainabilityField trip

Abstract

fetched live from OpenAlex

Urban environmental education (UEE) as a sub-genre of environmental education is still a relatively novel field of study, but an especially relevant one in Canada given its population’s concentration in urban centres. Rather than perpetuating the trope of urban centres as environmentally deficient, UEE presents an opportunity to empower urban residents toward learning and acting sustainably in vibrant and interconnected urban social-ecological systems and landscapes. Participant interviews were conducted with eight Metro Vancouver UEE practitioners and analyzed using a hermeneutic phenomenology approach to elucidate their experiences and propose how they may inform emergent practice. As major Canadian cities increasingly infuse their strategic plans and land-use decisions with environmental targets, further study of UEE in Metro Vancouver would enhance the planning and programming capacity of policy-makers, not-for-profits, educators, all levels of government, and all other interested stakeholders.

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)0.004
metaresearch head score (Gemma)0.010
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: Other · Consensus signal: none
Teacher disagreement score0.545
Threshold uncertainty score0.906

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0300.014
Scholarly communication0.0080.003
Open science0.0020.009
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0030.000

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 head0.007
GPT teacher head0.205
Teacher spread0.198 · 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
GenreOther

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

Citations0
Published2022
Admission routes1
Has abstractyes

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