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Record W2155892427 · doi:10.7202/006888ar

The Effect of Formal Versus Informal Job Security on Employee Involvement Programs

2003· article· en· W2155892427 on OpenAlexaffvenue
Gil A. Preuss, Brenda A. Lautsch

Bibliographic record

VenueRelations industrielles · 2003
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsJob satisfactionJob securityEmployee researchBusinessMetropolitan areaTest (biology)Employee engagementPerceptionGovernment (linguistics)Job insecurityPublic relationsControl (management)Set (abstract data type)PsychologyManagementSocial psychologyPolitical scienceWork (physics)Economics

Abstract

fetched live from OpenAlex

This study examines the effect of employee involvement and job insecurity on employee satisfaction and commitment. A data set incorporating information from employees, managers and government sources in fifteen hospitals in a single metropolitan region in the United States is used to test these issues. In contrast to previous research, we find that workers’ satisfaction and commitment persist as long as the form of employee involvement in place increases worker input and control in their jobs and as long as management is perceived to be making clear efforts to enhance the future security of workers’ jobs. Employee perception of management effort to maintain employment security, however, is based on past downsizing within the organization, thus raising the potential that continued downsizing will increase insecurity and therefore will decrease both employee desire to participate in decision-making, as well as employee satisfaction and commitment to the organization.

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)0.003
metaresearch head score (Gemma)0.020
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 score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.055
GPT teacher head0.359
Teacher spread0.304 · 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

Citations38
Published2003
Admission routes2
Has abstractyes

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