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Record W7098021677

doi:10.1155/2010/491368 Research Article Mentoring Experiences of Aging and Disability Rehabilitation

2013· article· en· W7098021677 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPsychology
TopicMentoring and Academic Development
Canadian institutionsnot available
Fundersnot available
KeywordsTheme (computing)RehabilitationFocus groupWork (physics)Career development
DOInot available

Abstract

fetched live from OpenAlex

which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Objectives. To explore research mentoring experiences and perceived mentoring needs of aging and disability researchers at different career stages. Design. Focus group and individual interviews with rehabilitation researchers at various career stages based in hospitals, universities, and hospital-based research institutes in Ontario, Canada. Results. The overall theme was mentoring for transition. Participants across career stages referred to helpful mentoring experiences as those that assisted them to move from their previous stage into the present stage or from the present stage into their next career progression. Unhelpful mentoring experiences were characterized by mentor actions that were potentially detrimental to transition. Subsumed under this theme were three categories. The first, “hidden information ” referred to practical information that was difficult to access. The second “delicate issues ” referred to helping the participant work through issues related to sensitive matters, the discussion of which could put the participants or their colleagues in a vulnerable position. The third category was “special challenges of clinicianresearchers”. Conclusions. Helpful mentoring for rehabilitation researchers working on concerns related to aging and disability

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.115
Threshold uncertainty score0.991

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)0.0100.000

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 head0.074
GPT teacher head0.409
Teacher spread0.335 · 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
Published2013
Admission routes1
Has abstractyes

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