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Record W4365814673 · doi:10.15402/esj.v8i4.70802

We are the Salmon Family: Inviting Reciprocal and Respectful Pedagogical Encounters With The Land

2023· article· en· W4365814673 on OpenAlexaffvenue
Cher Hill, Neva Whintors, R. Bailey

Bibliographic record

VenueEngaged Scholar Journal Community-Engaged Research Teaching and Learning · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous and Place-Based Education
Canadian institutionsAssembly of First NationsSimon Fraser University
Fundersnot available
KeywordsIndigenousReciprocalParticipatory action researchEmbodied cognitionAction (physics)Environmental ethicsCitizen journalismSociologyEcologyPolitical scienceAnthropologyEpistemologyLaw

Abstract

fetched live from OpenAlex

Through this action research project, we endeavour to reconfigure pedagogical encounters involving children and the natural world to be more reciprocal and respectful, as well as responsive to the ecological crisis. The goal of our research is to advance understandings of how to educate children to become good relatives to all the beings on these Lands. We are guided by the question: How can we educate children to live like Salmon People (those Indigenous to this place), which is the sacred responsibility of all those residing on the Coast Salish territories? Practices that contributed to shifting relationship between people and the Land and moved our community beyond our human-centric engagement were participatory and embodied. They included acts to care for Salmon and other beings as relatives, as well as experiencing Land as agential and existing independently of human desire. We see our research as a site for what Kari Grain calls “critical hope.”

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)0.780
metaresearch head score (Gemma)0.281
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Scholarly communication, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.613
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.7800.281
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.6130.001
Scholarly communication0.0020.001
Open science0.0010.000
Research integrity0.0000.467
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 head0.250
GPT teacher head0.430
Teacher spread0.180 · 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 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

Citations2
Published2023
Admission routes2
Has abstractyes

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