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Record W4404136917 · doi:10.1080/15505170.2024.2419134

Grounded governance: Cultivating social justice through community-engaged learning with PEPAKEN HÁUTW (Blossoming Place)

2024· article· en· W4404136917 on OpenAlexaff
Sarah Wiebe

Bibliographic record

VenueJournal of Curriculum and Pedagogy · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicService-Learning and Community Engagement
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsSocial justiceSociologyCorporate governanceEnvironmental justiceEconomic JusticePedagogyPolitical scienceCriminologyBusinessLaw

Abstract

fetched live from OpenAlex

By deepening student relationships to local governance systems, they become better equipped to envision and enact the worlds they seek to create. This paper discusses a community-engaged learning initiative facilitated by a University of Victoria instructor that centered on the theme of “Grounded Governance” to anchor student learning about governance and social justice theories, movements and practices. The overall approach draws inspiration from bell hooks who explains the value and significance of engaged learning. Specifically, this paper discusses the experience of teaching place-based learning through engagement with Indigenous-led ecological restoration efforts, including collaboration with PEPAKEṈ HÁUTW̱ (Blossoming Place). The author reflects on community site visits with a W̱SÁNEĆ nonprofit organization to learn about ecological restoration and decolonial governance. This grounded approach to teaching is inspired by Indigenous-led place-based learning. As a collaborative effort between the Studies in Social Justice program, the School of Public Administration and community partners, this pedagogy aims to integrate community-engaged learning more deeply into the study of public administration. Doing so in practice emphasizes relationship-building with local Indigenous-led community organizations while supporting student learning objectives by teaching about social justice through collaborative and meaningful public engagement.

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)0.008
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.316
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0080.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.006
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 head0.047
GPT teacher head0.370
Teacher spread0.323 · 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.

Study designQualitative
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

Citations1
Published2024
Admission routes1
Has abstractyes

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