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Record W4306818383 · doi:10.1108/ijmce-01-2022-0004

The role and place of mentorship for young people with blindness and low vision in educational contexts

2022· article· en· W4306818383 on OpenAlexaffabout
Melissa Cain, Danika Rhiannon Blackstock, Melissa Fanshawe, Mahadeo A. Sukhai, Ainsley Latour

Bibliographic record

VenueInternational Journal of Mentoring and Coaching in Education · 2022
Typearticle
Languageen
FieldPsychology
TopicMentoring and Academic Development
Canadian institutionsCNIB Foundation
Fundersnot available
KeywordsMentorshipBlindnessOriginalityFocus groupValue (mathematics)Qualitative researchPsychologyPedagogyMedical educationSociologyMedicineSocial scienceOptometry

Abstract

fetched live from OpenAlex

Purpose The purpose of this article is to understand the role and value of mentorship for young people with blindness and low vision (BLV) through their education and work journey and to provide a conceptual framework for developing mentoring opportunities for young people with BLV. Design/methodology/approach Experiences of formal and informal mentorship were gathered within two distinct groups: adolescents with BLV in Australia and young adults with BLV in Canada. Qualitative data were collected from semi-structured individualized interviews regarding the experiences, understanding, and valuing of mentorship within these groups. Findings Results indicate the importance of informal role models and formal mentors within the lives of participants and how these become more refined and specific over time. Australian students valued role models as examples of success and inspiration for their own goals. Canadian mentees desired mentors as examples of personal lived experiences and providers of career-specific advice. Originality/value The study is original in its focus on the role of mentors for young people with blindness or low vision.

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.090
Threshold uncertainty score0.214

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.010
GPT teacher head0.325
Teacher spread0.315 · 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 designObservational
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
Published2022
Admission routes2
Has abstractyes

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