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Record W7133071389

Exploring Relationships Between PhD Students’ Career Aspirations and Persistence Towards the Degree

2025· dissertation· W7133071389 on OpenAlexaboutno aff
Monica Munaretto

Bibliographic record

VenueTSpace · 2025
Typedissertation
Language
FieldHealth Professions
TopicDoctoral Education Challenges and Solutions
Canadian institutionsnot available
Fundersnot available
KeywordsPersistence (discontinuity)Career PathwaysThematic analysisCareer developmentQualitative researchCareer portfolioCareer counselingSocial cognitive theoryGraduate students
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this study is to explore how doctoral students develop career aspirations and how these relate to their persistence and degree completion. The PhD is widely viewed as preparation for faculty careers yet evidence indicates less than one quarter of Canadian PhDs will be employed as tenure-track professors. How PhDs enter the labour market is a topic of great national interest as universities and governments seek to improve PhD career outcomes. This Exploratory Descriptive Qualitative study involved semi-structured interviews with 31 domestic upper-year doctoral students in the fields of Biology and English in Ontario Universities. The Social Cognitive Career Theory (SCCT) Choice Model informed the design of the study, providing a lens through which to interpret the findings. Thematic analysis was used to interpret interviews, resulting in themes related to student motivation, well-being, exploration of diverse careers, career education, professional development, and person influences on graduate student career aspirations. Findings indicate doctoral student career aspirations evolve over the course of the degree and participants felt strong links between their career aspirations and persistence to complete the degree, even when they did not have well-articulated career plans. Study participants experienced the stages, processes and feedback loops proposed by the SCCT Choice Model yet it was found the model does not adequately illustrate the complex pathways and experiences of parallel planning described by participants nor the influence of career aspirations on intentions to persist to degree completion. As a result, a new model - the PhD Career Aspirations and Persistence Model - is presented. In addition to the new model, the study resulted in unexpected findings contributing to the field. First, while extended time to completion may be viewed negatively by researchers and administrators, some students strategically delay graduation for career-related reasons. Second, despite institutions’ efforts to develop valuable career education for non-academic roles, some students experience unintended consequences related to these activities including frustration, overwhelm and sadness. Finally, while participants seeking faculty-roles reported adequate on-campus support, students seeking non-faculty roles often relied on their own resourcefulness in career exploration. Implications for practice and recommendations for further study are provided.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gptno category
Domain: not available · Genre: Other
About the Canadian research system: no · About a Canadian topic: no
Other designlow
grokno category
Domain: not available · Genre: Other
About the Canadian research system: no · About a Canadian topic: no
Other designlow
opusMetaresearch
Domain: Incentives · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
models splitAgreement compares identical category sets and study designs across arms.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.399
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0090.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0010.000

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 head0.921
GPT teacher head0.573
Teacher spread0.348 · 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

Labeled directly by 3 models reading the full record.

Metaresearch

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designOther design · Observational
DomainIncentives
GenreOther · Empirical

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
Published2025
Admission routes1
Has abstractyes

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