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Record W2971158098 · doi:10.1177/1038416219828087

Career development for doctoral and postdoctoral trainees in Canada

2019· article· en· W2971158098 on OpenAlexaffabout
Charles P. Chen, Aleksandra Lalovic

Bibliographic record

VenueAustralian Journal of Career Development · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicCareer Development and Diversity
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCareer developmentPaceCareer PathwaysCareer counselingMedical educationPedagogyPopulationCareer portfolioPsychologySociologyMedicine

Abstract

fetched live from OpenAlex

The career landscape for doctoral and postdoctoral trainees has significantly changed in recent decades. There is now an oversupply of PhD graduates in the science and engineering fields relative to the availability of academic positions, and jobs outside of academia have now become the norm. Doctoral training programmes have failed to keep pace with this change, and many trainees who are forced to rethink academic career aspirations feel unprepared for today’s job market. Intertwined with this are challenges associated with life stage and school-to-work transition, which make the career development issues facing doctoral and postdoctoral trainees unique and complex. The aim of this article is to shed light on these issues and to examine them through the lens of career development theories. Social cognitive career theory offers insight into the factors that influence career development in doctoral and postdoctoral trainees, and narrative career counselling can serve as a valuable intervention for this population to help shape their future career, whether within or outside of academia.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.679
Threshold uncertainty score0.995

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 studies0.0000.000
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 head0.065
GPT teacher head0.268
Teacher spread0.203 · 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

Citations7
Published2019
Admission routes2
Has abstractyes

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