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Record W3209042411

Pre-Service Teachers’ Perceptions And Expectations of K-12 Schooling Locales in Saskatchewan

2020· dissertation· en· W3209042411 on OpenAlexaboutno aff
Patrick Jordan Nikulak

Bibliographic record

VenueoURspace (University of Regina) · 2020
Typedissertation
Languageen
FieldSocial Sciences
TopicEducation Systems and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsPerceptionService (business)PsychologyMathematics educationGeographyPolitical scienceBusinessMarketing
DOInot available

Abstract

fetched live from OpenAlex

The expectations which teachers hold affect their everyday decisions and, ultimately, the classroom, their instruction, the school, and the communities in which they serve. While there has been research into teachers’ expectations of locales of schooling in other parts of the world, there has been little research into the expectations that undergraduate education students hold towards specific locales of schooling within Saskatchewan. I conducted an exploratory phenomenographical study by interviewing four undergraduate students in the Faculty of Education at the University of Regina to learn more about their expectations and perceptions of band, rural, and urban locales of schooling in Saskatchewan. Participants thought most about their expectations of how the locales would affect their personal lives, professional anxieties, professional opportunities, relationships within the context of teaching, and the resources they were expecting to be available. Their knowledge of these locales was either through direct first-hand experience or anecdotally through friends and colleagues, rarely through their university program. Locales not directly accessible to the participants, often band, were most often learned about indirectly, for example, through friends or family members with direct experience. The four participants, regardless of prior education or experience, preferred to teach in urban schools first, rural schools second, and band schools third.

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)0.000
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 score0.381
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.020
GPT teacher head0.289
Teacher spread0.269 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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