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Record W4386690890 · doi:10.1108/et-06-2021-0235

A dynamic capability view of career adaptation: an exploratory study

2023· article· en· W4386690890 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEducation + Training · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education and Employability
Canadian institutionsUniversity of CalgaryUniversity of GuelphMount Royal University
Fundersnot available
KeywordsEmployabilityAdaptation (eye)OriginalityDelphi methodAdaptabilityKnowledge managementDynamic capabilitiesPsychologyCareer developmentExploratory researchEmpirical researchComputer scienceApplied psychologySociologyPedagogyManagementSocial psychologyArtificial intelligence

Abstract

fetched live from OpenAlex

Purpose Disruptive forces, such as the global pandemic and technological innovation, are leading to growing labor uncertainty. For organizations, being able to adapt is a key skill for employees, while adapting to different employment contexts is increasingly essential for career success. This study leverages career adaptability theory and integrated dynamic capabilities to isolate skills enabling career adaptation. Design/methodology/approach A qualitative study was conducted to develop a skills codebook using a Delphi technique to converge on career adaptation skills, which was validated against leading meta-skills frameworks and a purposeful sample of 15 occupational competency models. Findings The codebook phase identified 24 distinct meta-skills in 6 clusters: problem-solving, self-reliance, collaboration, communication, core literacies and core workplace skills. Findings confirmed that most of the skills identified by the experts were also present across the meta-skills frameworks. Research limitations/implications This study highlights research opportunities, including a recommendation to extend the codebook by conducting a large sample empirical study of occupational competency models. Practical implications Adaptive individuals remain attractive in the job market. With the proposed framework, individuals can systematically reflect on ways to develop career adaptation skills. Other stakeholders should support the development of skills that facilitate an individual's capacity to adapt to diverse employment contexts. Originality/value This study contributes to resolving the debate on skills contributing to career adaptation by combining the career adaptability theory and integrated dynamic capabilities, to produce a harmonized meta-skills codebook including labels, definitions and synonyms. This study validates the codebook against leading skills frameworks and occupational competency models.

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.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.186
Threshold uncertainty score0.576

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.182
GPT teacher head0.419
Teacher spread0.237 · 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