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Record W4367021252 · doi:10.1007/978-3-031-25584-7_20

Science Teacher Education in Canada: Addressing Diversity by Living and Teaching Intersectionality

2023· book-chapter· en· W4367021252 on OpenAlexaffabout
Lydia Burke

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicIndigenous and Place-Based Education
Canadian institutionsUniversity of Toronto
FundersSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
KeywordsScience educationPedagogyDiversity (politics)SociologyMathematics educationPsychology

Abstract

fetched live from OpenAlex

Abstract As a Black woman of Caribbean heritage, born and raised in England, my own school science experience was focused on learning the tricks that teachers presented as intuitively graspable. I was used to pushing through and ignoring the ‘outsider’ feelings that I possessed. As a science teacher and science teacher educator, I came to understand that there are many students for whom the acquisition of science knowledge means compromise to their sense of selfhood, either because they are members of groups for whom Western modern science is not a central tenet of understanding or because of the esoteric mode of science instruction. In this chapter, I identify four critical incidents that have occurred during my professional experience as a science teacher educator. I explore the implications of these incidents by examining them through the equity lens of intersectionality to highlight broader concerns in science teaching and science teacher education. The analyses reinforce the need for science teachers to allow themselves and their students to be open and reflective about their own positionings in the field of science education as well as the need to acknowledge the historical and philosophical contexts of Western modern science as a body of knowledge. I hope that this chapter will be used by science teacher educators to stimulate dialogue and provide an artifact around which constructive and meaningful conversation foments in the many spaces of science teacher education.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.416
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.036
GPT teacher head0.298
Teacher spread0.262 · 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 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

Citations1
Published2023
Admission routes2
Has abstractyes

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