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Record W4312186646 · doi:10.37119/ojs2022.v28i1b.651

Embracing Our Power: ECE Students’ Experiences Creating Spaces of Resistance in Post-Secondary Institutions

2022· article· en· W4312186646 on OpenAlexaffvenueabout
Camila Casas Hernandez, Luyu Hu, Tammy Primeau McNabb, Grace Wolfe

Bibliographic record

Venuein education · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicTeacher Education and Leadership Studies
Canadian institutionsEducation and Early Childhood DevelopmentToronto Metropolitan University
Fundersnot available
KeywordsResistance (ecology)PoliticsSociologyAgency (philosophy)Identity (music)Power (physics)PedagogyNarrativePolitical sciencePublic relationsSocial scienceLaw

Abstract

fetched live from OpenAlex

In this paper, we, four students with diverse social locations, explore the development of preservice educators’ professional identities as political resisters. Through our experiences in an Ontario college, we found commonality in our emerging need to resist “alarming discourses” (Whitty et al., 2020, p. 8). By dissecting and analyzing the neoliberal narrative perpetuated by our educational institution, we refused the notion of being the good ECE (Langford, 2007). Rejecting the universalism and totalism of Western European curricular and pedagogical inheritances, we set out to create a space to embrace alternative narratives to critically question our role and the expectations of our profession in a neoliberal world. This space was used for ECEC advocacy and brought together our student community, creating an opportunity to mentor while fostering human connections from our stories. Through collaboration, we reaffirm the importance of building community and reciprocal mentorship for nurturing and developing political agency within our field. We are motivated to sustain this critical space, to serve as a place of resistance for other students who question “universal truths.” Education comes from more than the diploma received. Keywords: Early childhood educators, professional identity, resistance, student advocacy, post-secondary institutions, ethics of care

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.114
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.074
GPT teacher head0.428
Teacher spread0.354 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2022
Admission routes3
Has abstractyes

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