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Record W4322506455

Mentorship and Induction: Negotiating a Collaborative Enterprise or Apprenticing for Status Quo Maintenance?

2010· article· en· W4322506455 on OpenAlexaboutno aff
Donatille Mujawamariya, John P. Portelli, R. Patrick Solomon, Sarah Elizabeth Barrett, Christine L. Cho

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2010
Typearticle
Languageen
FieldPsychology
TopicMentoring and Academic Development
Canadian institutionsnot available
Fundersnot available
KeywordsStatus quoMentorshipNegotiationTeacher inductionBusinessPolitical scienceMedicineMedical educationProfessional development
DOInot available

Abstract

fetched live from OpenAlex

This paper is from a three-year research project that examined the Ontario (Canada) government philosophy, policy and practice in moving from standardized teacher testing to a new teacher induction program (NTIP) to achieve teacher quality and competence. This paper utilizes a critical democratic perspective to analyze the perspectives of 47 teacher educators from 10 faculties of education in Ontario. Two major themes arose from their perspectives on NTIP: a) clear collaboration/partnership among stakeholders (including faculty, school boards, schools, communities); and, b) increasing effective communication and knowledge while maintaining the importance of equity, diversity and understanding community. The findings revealed the need for a more critical examination of the process and outcome of mentorship and induction programs for new teachers.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.058
metaresearch head score (Gemma)0.064
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.058
Threshold uncertainty score0.306

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0580.064
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0190.053
Scholarly communication0.0190.022
Open science0.0030.017
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0070.001

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 head0.223
GPT teacher head0.559
Teacher spread0.336 · 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 source (direct Gemma or distilled Codex), 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

Citations3
Published2010
Admission routes1
Has abstractyes

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