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Record W2768867613 · doi:10.1111/1748-8583.12175

Balancing tensions: Buffering the impact of organisational restructuring and downsizing on employee well‐being

2017· article· en· W2768867613 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

VenueHuman Resource Management Journal · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicOrganizational Downsizing and Restructuring
Canadian institutionsTrinity College
Fundersnot available
KeywordsRestructuringStructural equation modelingWork (physics)BusinessPerceptionHuman resource managementPsychologyMarketingManagementEconomicsComputer scienceEngineering

Abstract

fetched live from OpenAlex

Abstract This study examines the impact of employee experiences of restructuring and downsizing on well‐being. The job demands‐resources model was used to develop hypotheses related to job demands in the form of work intensity and job resources in the form of consultation. The job demands‐resources model allows for direct incorporation of employee perceptions and does not assume a singular, predetermined consequence of HRM practices. Hypotheses were tested via structural equation modelling on a nationally representative sample of over 5,110 employees from the Republic of Ireland in 2009. The findings indicate that work intensity serves as a conduit through which experiences of restructuring and downsizing negatively impact employee well‐being. Notably, consultation served as a buffer, diminishing the extent of this negative experience. The findings illuminate the complex pathways that shape how restructuring and downsizing are perceived by employees and the consequences for well‐being. We discuss the theoretical and managerial implications of these findings.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.175
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.000
Scholarly communication0.0020.001
Open science0.0010.001
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 head0.015
GPT teacher head0.252
Teacher spread0.236 · 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