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Record W7037124993

The current state is a crime: Decolonizing experiential education on the Brock University campus

2023· other· en· W7037124993 on OpenAlexafffundabout

Bibliographic record

VenueBrock University Digital Repository (Brock University) · 2023
Typeother
Languageen
FieldEnvironmental Science
TopicAnimal Ecology and Behavior Studies
Canadian institutionsBrock University
FundersBrock University
KeywordsExperiential learningExperiential educationIndigenousGovernment (linguistics)Participatory action researchState (computer science)DecolonizationHigher education
DOInot available

Abstract

fetched live from OpenAlex

Indigenous ways of knowing and being have always been experiential. With this, our Canadian post-secondary institutions that have been working to grow experiential education and experiential learning opportunities have an obligation to acknowledge these Indigenous roots in order to avoid further appropriation. With two thirds of the Truth and Reconciliation Commission (TRC) of Canada’s 94 calls to action focused on education, including post-secondary, the Ontario Government has also recommended that post-secondary institutions in the province provide students with a minimum of two experiential learning opportunities within their academic courses by the time they graduate. This Participatory Action Research (PAR) project at Brock University was designed and executed in full collaboration with Indigenous peoples and looks at a campus with a focus on decolonization as well as experiential learning through an Appreciative Inquiry framework to best determine how experiential education can be decolonized. Using semi-structured interviews, focus groups, and institutional documents that speak to the current state of experiential learning as well as institutional strategic goals, ten themes were developed. These highlight settler tendencies, the current state of experiential education, recommendations for decolonization and an ideal future state, important approaches to consider when decolonizing as an individual and as a campus, cautions to heed, as well as values and emotions to consider. In order to decolonize experiential learning and the campus authentically, Indigenous voices must be and have been amplified in this process.

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)0.011
metaresearch head score (Gemma)0.011
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: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.956
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0250.038
Scholarly communication0.0110.007
Open science0.0020.015
Research integrity0.0020.005
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 head0.012
GPT teacher head0.213
Teacher spread0.202 · 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
Published2023
Admission routes3
Has abstractyes

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