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Record W2587449112

A Short History of the Institute for Environmental Learning at Simon Fraser University

2016· article· en· W2587449112 on OpenAlexfundno aff
John Joshu Coward

Bibliographic record

VenueSummit (Simon Fraser University) · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical Geography and Geographical Thought
Canadian institutionsnot available
FundersSimon Fraser University
KeywordsHistory
DOInot available

Abstract

fetched live from OpenAlex

This paper outlines the creation and evolution of the Institute of Environment Learning at Simon Fraser University from 2006 to 2016. From its inception in 2006, as the BC Working Group and Network on Sustainability Education, to obtaining RCE status in May 2010 and to be formally approved as a research institute by the Simon Fraser University Senate later that year, the goal of the educators involved was to develop and support research on environmental learning in communities, schools and post secondary institutions throughout the province of British Columbia. Along the way, members have gone in different directions and as a participant in this process; I have documented this narrative in this paper to help bring parties more closely together again and have also recommended governance, operational and fundraising model for the institute for the same purpose.

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)0.007
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.967
Threshold uncertainty score0.238

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0060.007
Science and technology studies0.0130.011
Scholarly communication0.0160.006
Open science0.0020.010
Research integrity0.0050.011
Insufficient payload (model declined to judge)0.0510.022

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 head0.015
GPT teacher head0.201
Teacher spread0.186 · 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 designNot applicable
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
Published2016
Admission routes1
Has abstractyes

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