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Record W2997121471

Weaving with Trickster: Indigenous students making our place in science

2019· dissertation· en· W2997121471 on OpenAlexaboutno aff
Ciara Morgan-Feir

Bibliographic record

VenueSummit (Simon Fraser University) · 2019
Typedissertation
Languageen
FieldPsychology
TopicScience Education and Perceptions
Canadian institutionsnot available
Fundersnot available
KeywordsTricksterWeavingIndigenousVisual artsEngineeringArtGeographyArchaeologyMechanical engineeringEcologyBiology
DOInot available

Abstract

fetched live from OpenAlex

Indigenous peoples, the fastest growing population in Canada, remain significantly underrepresented in science related post-secondary education fields.This underrepresentation poses challenges for the goals of self-determination and equal participation in a society that is becoming increasingly specialized and technologically advanced.As a Métis-Irish teacher and learner of science, I frequently found myself at intersections of different worlds in my own education.Through this study, with guidance from the trickster Raven, I explored each of those intersections and their impacts on the experiences of other Indigenous science students.This study is best described as multiple layers of theory and practice woven together.In the first half of this dissertation, education research on student retention at postsecondary is woven into education research on school science curriculum.In the second half, the stories of seven Indigenous science students are woven together, along with my own story, weaving a sash of student experience.Informed by Lowan-Trudeau's (2012) notion of the 'spirit of métissage', I examine student stories from the starting point of an assumption of similarity.Employing multiple styles of métissage (mixing or weaving) as the primary methodology of this study, I blend Indigenous storywork and self-study methodologies.The results of this study expose resonances with the literature in student retention and cultural relevance, along with resonances between student stories.Particularly compelling findings include that for many of the students interviewed, participating in Western science involved creating their own space between Indigenous and Western knowledge traditions.The students took great efforts to decolonize their own education, describing their (w)holistic worldviews as a strength rather than a liability, and making efforts to educate misinformed or even racist opinions from classmates and educators.This is evidence of the fact that the university has not yet achieved the decolonizing goal of creating safe educational spaces for Indigenous students.These Indigenous students found themselves tremendously supported by relationships with educators, family members, and Indigenous staff and peers, and repeatedly emphasized the importance of such connections to their success in post-secondary science.This is evidence of the primacy of relationship for many Indigenous students, and provides a starting point for members of the university science community, both Indigenous and non-Indigenous, to support the success of these learners.v

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)0.005
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.994
Threshold uncertainty score0.252

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0310.020
Scholarly communication0.0100.007
Open science0.0030.011
Research integrity0.0030.008
Insufficient payload (model declined to judge)0.0030.001

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 head0.026
GPT teacher head0.332
Teacher spread0.306 · 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.

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

Citations0
Published2019
Admission routes1
Has abstractyes

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