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Record W4388972812 · doi:10.1108/cdi-04-2023-0099

Reconstruction work awaits: work identity in the aftermath of health-related career shock

2023· article· en· W4388972812 on OpenAlexaff
Pamela Suzanne, Viktoriya Voloshyna, Jelena Zikic

Bibliographic record

VenueCareer Development International · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsYork UniversityThompson Rivers University
Fundersnot available
KeywordsOriginalityIdentity (music)PsychologyLiminalityIdentity formationMultinational corporationCoping (psychology)PhenomenonSocial psychologyInterpretative phenomenological analysisShock (circulatory)SociologyQualitative researchSelf-conceptEpistemologyPolitical scienceMedicinePsychotherapistAestheticsSocial science

Abstract

fetched live from OpenAlex

Purpose This paper aims to explore the stages and processes of work identity reconstruction following a major health-related career shock. Design/methodology/approach In-depth case study and interpretive phenomenological methods are used to allow for deep reflective self-analysis of post-career shock stages. The paper explores the identity processes and stages a Chief of Human Resources of a multinational firm experienced after being deprived from his main working abilities as a result of a brain stroke. Findings Post-shock work identity stages and processes are identified, as long as the importance of identity threat, liminality, identity internalization and relational recognition in the reconstruction process. The findings propose new coping responses that may allow individuals to escape a diminished work identity: identity shedding and identity implanting. Originality/value While career shocks play a significant role in career development, there is currently little understanding of how career shocks may affect individuals' work identity or sense of self, particularly over time. The paper provides a nuanced understanding of this phenomenon, through process data collected at several points in time over a period of 14 years.

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 score0.021
Threshold uncertainty score0.743

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.036
GPT teacher head0.256
Teacher spread0.221 · 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

Citations8
Published2023
Admission routes1
Has abstractyes

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