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Record W1534449848 · doi:10.37119/ojs2013.v19i2.138

Exploring the Experiences of a Small Group of Saskatchewan Neophyte Aboriginal Teachers

2014· article· en· W1534449848 on OpenAlexaffvenueabout
Laurie-ann M. Hellsten, Jane P. Preston, Michelle Prytula, Danielle P. Jeancart

Bibliographic record

Venuein education · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsUniversity of Prince Edward IslandUniversity of Saskatchewan
Fundersnot available
KeywordsMentorshipLikert scalePsychologyAutonomyUnit (ring theory)Focus groupWorkloadMedical educationPlan (archaeology)PedagogyMathematics educationSociologyMedicineManagementPolitical science

Abstract

fetched live from OpenAlex

The purpose of this paper is to explore the experiences of a small group of Aboriginal neophyte teachers in Saskatchewan, Canada. Part of a larger study, this research used a mixed method approach for data collection in which 18 Aboriginal beginning teachers completed a survey (with Likert-scale items and open-ended questions) and an additional two Aboriginal beginning teachers participated in individual interviews. This study is a focused attempt to highlight the voices of the Aboriginal beginning teachers. Findings suggested that many participants had difficulty obtaining employment and identified family and friends as their core supports. Most participants felt challenged by their workload and a lack of supports to address the diverse needs of their students. Most participants found teaching to be rewarding and enjoyed the autonomy of their own classrooms. Many of the issues raised by the participants can be addressed by placing a greater focus on an Aboriginal epistemology based on the concept of community. To promote Aboriginal teacher recruitment, employment, and retention rates, it is essential that neophyte teachers are provided with employment assistance, mentorship opportunities, and curricular and unit plan resources. Keywords: neophyte/beginning teachers; preservice teacher education, mixed-methodology

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 score0.343
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.029
GPT teacher head0.315
Teacher spread0.286 · 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
Published2014
Admission routes3
Has abstractyes

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