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Record W1995905266 · doi:10.1177/0170840611421250

Cross-Level Dynamics between Changing Organizations and Career Patterns of Reduced-Load Professionals

2011· article· en· W1995905266 on OpenAlexaff
Jean‐Baptiste Litrico, Mary Dean Lee, Ellen Ernst Kossek

Bibliographic record

VenueOrganization Studies · 2011
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicLabor market dynamics and wage inequality
Canadian institutionsMcGill UniversityQueen's University
Fundersnot available
KeywordsDynamics (music)Work (physics)Decoupling (probability)Context (archaeology)Career developmentBusinessMarketingPublic relationsDemographic economicsEconomicsPsychologySocial psychologyPolitical scienceEngineering

Abstract

fetched live from OpenAlex

Integrating research on careers, flexible work arrangements, and open systems views of organizational change, we investigate how evolution in the broader organizational context interacts with professional career trajectories over time. Interviews were conducted six years apart (1997 and 2003) with 17 major employers in North America and 36 managers and professionals in those firms who were working on a reduced-load basis by choice in 1997. Overall, we found that career patterns are impacted by the dynamic combination of individual-level and contextual factors. Specifically, while changes in core business/client base, internal structure changes, and industry turbulence were associated with higher proportions of returns to full-time work, financial threat was associated with lower levels of return to full-time work. We identified four cross-level dynamics (co-optation, synergy, decoupling, and tug of war) that capture different patterns of interaction between individual work arrangement trajectories and larger trends occurring at the organizational or industry level.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.094
Threshold uncertainty score0.591

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.097
GPT teacher head0.291
Teacher spread0.194 · 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

Citations11
Published2011
Admission routes1
Has abstractyes

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