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High‐Commitment Work Practices and Downsizing Harshness in Australian Workplaces

2007· article· en· W2048294388 on OpenAlexaff
Roderick D. Iverson, Christopher D. Zatzick

Bibliographic record

VenueIndustrial Relations A Journal of Economy and Society · 2007
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicOrganizational Downsizing and Restructuring
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsWorkforceWork (physics)HarshnessSample (material)TurnoverBusinessLabour economicsDemographic economicsWork hoursPublic relationsEconomicsPolitical scienceManagementWorking hoursEconomic growthEngineering

Abstract

fetched live from OpenAlex

This study examines the relationship between high‐commitment work practices (HCWP) and downsizing. The results based on a large, representative sample of Australian workplaces supported our predictions. Consistent with previous research, HCWP was positively related to workforce reduction. However, workplaces with more HCWP used less harsh strategies (e.g., more employee‐friendly approaches to downsizing) such as voluntary layoffs and early retirement than the harsher strategy of compulsory layoffs. The implications of these findings are discussed.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.037
GPT teacher head0.249
Teacher spread0.211 · 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 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

Citations47
Published2007
Admission routes1
Has abstractyes

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