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Record W7033785819

From Resisting to Sustaining: Exploring Skilled Migrants’ Alternative Career Pathways

2024· other· en· W7033785819 on OpenAlexaboutno aff

Bibliographic record

VenueYork University Digital Library (York University) · 2024
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsCareer PathwaysEmployabilityCareer developmentIdentity (music)Career pathNegotiationMeaning (existential)Career counseling
DOInot available

Abstract

fetched live from OpenAlex

This qualitative study employs a grounded theory approach to explore the lived experiences of skilled migrants in Canada who engage in alternative careers. The study investigates identity work and meaning-making processes of career actors who perceive alternative career options as “beginning again.” Through 30 semi-structured in-depth interviews, the findings identify three distinct alternative career pathways: provisional, experimental, and reformist; each characterized by a unique form of identity work and accompanying types of meaning-making. Each path provides distinctive insights into how skilled migrants cope with, and adapt to, the mismatches between their skills and new job demands, challenging and redefining their professional identities. Additionally, it highlights how each career pathway may shape migrants’ subjective well-being. This study advances the existing literature on major career transitions, specifically skilled migrant career trajectories inside local organizations, by highlighting how they reconstruct new professional identities and derive meaning in contexts that often fall below their qualifications and career aspirations. This study extends existing research on employability and career sustainability by integrating the dynamic processes of identity negotiation and meaning-making in the face of career transitions. It also builds on the existing meaning-making literature by highlighting the career narratives of those who must search for new meanings while pursuing “less than ideal” career opportunities. Finally, the findings provide practical implications related to outcomes of alternative career opportunities on migrant career success and, more broadly, for employers and policymakers.

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)0.005
metaresearch head score (Gemma)0.006
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.102
Threshold uncertainty score0.202

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0180.012
Scholarly communication0.0070.004
Open science0.0020.007
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.048
GPT teacher head0.184
Teacher spread0.136 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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