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Record W2908885710

A Pan-Canadian Look at the Experiences Over the First Five Years For Early-Career Teachers.

2018· article· en· W2908885710 on OpenAlexaffabout
John Gino Bosica, Ian Matheson, Keith Walker, Benjamin Kutsyuruba

Bibliographic record

Venue2018 Conference of the Canadian Society for the Study of Education · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicTeacher Professional Development and Motivation
Canadian institutionsUniversity of SaskatchewanUniversity of ReginaQueen's University
Fundersnot available
KeywordsMentorshipTeacher inductionFeelingCareer developmentCareer PathwaysMedical educationPedagogyPsychologyProfessional developmentMedicineSocial psychology
DOInot available

Abstract

fetched live from OpenAlex

In 2016, a pan-Canadian study was conducted to examine the experiences of new teachers during their induction to the profession. In total, 1,343 teachers responded to a survey that contained information regarding their experiences with mentorship, administration, career development, and induction programs during their first five years as a teacher. The survey represents a part of a three-year pan-Canadian research project focused on the impact of induction and mentorship programs in early-career teachers. This paper draws on the survey data from the pan-Canadian study to examine the differences in experiences, beliefs, and feelings held by teachers throughout the first five years in the profession . Specific differences among teachers across the first five years in the profession were found in reported experience s with career support, school environment, and attitudes regarding the profession. This paper contributes to our understanding of how best to support early-career teachers, and provides insight about the experience of being a new teacher across Canada.

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 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 score0.347
Threshold uncertainty score0.998

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 studies0.0030.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.059
GPT teacher head0.316
Teacher spread0.257 · 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 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
Published2018
Admission routes2
Has abstractyes

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