MétaCan
Menu
Back to cohort

Career regret and career sacrifice: the less examined yet ever-present career experiences

2021· article· en· W3183622457 on OpenAlexaboutno aff
John Blenkinsopp, Alexandra Budjanovcanin, Michael Clinton, Jelena Zikic

Bibliographic record

VenueAcademy of Management Proceedings · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicHuman Resource and Talent Management
Canadian institutionsnot available
Fundersnot available
KeywordsRegretSacrificeFeelingCareer developmentPsychologyManagementSocial psychologyComputer scienceHistory

Abstract

fetched live from OpenAlex

This symposium explores career regret and career sacrifice – phenomena experienced by many individuals throughout the course of their working lives. Career regret is the feeling of wishing to undo a past decision made in one’s career, whereas career sacrifice involves a decision to give something up in one’s career. These related career experiences have both been relatively under-explored in the field of careers and organisational behaviour (Byington, Felps and Baruch, 2019). However, their prevalence and their potential to impact on the careers and well-being of career actors, especially in the current turbulent climate, calls for a better understanding of these phenomena. Scholars in this symposium have been united in their motivation to further understand these phenomena and their individual and organisational consequences The Remains of the Day: Dealing with Regret in Later Career Presenter: John Blenkinsopp; Newcastle Business School, Northumbria U. Presenter: Shuo Wang; Newcastle Business School, Northumbria U. Presenter: Olaolu Eniola; Newcastle Business School, Northumbria U. Regret’s consequences: The performance of Regret Workers Presenter: Alexandra Budjanovcanin; King's College London Presenter: Chris Woodrow; Henley Business School, U. of Reading Higher role performance… but higher partner self-sacrifice too. Does worker self-sacrifice pay off? Presenter: Michael Clinton; King's College London Unpacking career sacrifice: From prosocial benefits to regret Presenter: Jelena Zikic; York U. Presenter: Soodabeh Mansoori; York U., Toronto

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.321
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.002
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 head0.054
GPT teacher head0.244
Teacher spread0.191 · 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.

Study designNot applicable
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

Citations1
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueAcademy of Management ProceedingsSame topicHuman Resource and Talent ManagementFrench-language works237,207