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Record W3083769069 · doi:10.21810/sfuer.v13i1.1216

Seeking to Engage

2020· article· en· W3083769069 on OpenAlexfundvenueaboutno aff
Michael Maser

Bibliographic record

VenueSFU Educational Review · 2020
Typearticle
Languageen
FieldPsychology
TopicOutdoor and Experiential Education
Canadian institutionsnot available
FundersSimon Fraser University
KeywordsContext (archaeology)InstitutionSociologyAffect (linguistics)Point (geometry)Natural (archaeology)Public relationsPolitical scienceEnvironmental ethicsGeographySocial scienceArchaeology

Abstract

fetched live from OpenAlex

Simon Fraser University, from the time of its opening in the 1960s, has striven to be a modernist and progressive educational institution. These characteristics are reflected in the architectural designs of its campuses, its epistemological orientations and offerings, and its policies. The university also states an ambition to be "Canada's most engaged university" on its website (sfu.ca/about.html). It is in considering this last point that this paper questions and considers SFU's 'engagement' in the context of the emerging environmental crisis. In particular, this paper focuses attention on the Burnaby Mountain campus and considers its place - geographically, architecturally, and culturally, and how these considerations of place intertwine and contribute or detract from a sense of engagement. Overall, this author posits that Simon Fraser's Burnaby Mountain campus is critically alienated from the in-situ forest that surrounds it, through character and gesture, and this is most unfortunate given a stated need by experts and educators to deepen engagement with natural environments in this time of crisis. Insights from place-based education identify that in-situ ecological knowledge, and insights arising from First Nations peoples, can help to grow new knowledge and awareness, deepen resiliency, and affect positive cultural change. The author suggests that Simon Fraser's Burnaby Mountain campus is an appropriate location to grow such a place-based education program and deepen its engagement in new, valuable ways.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.748
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0300.013

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 head0.073
GPT teacher head0.437
Teacher spread0.364 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreCommentary

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
Published2020
Admission routes3
Has abstractyes

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