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Record W2024366021 · doi:10.1002/tie.1010

An International Comparison of Employee Welfare Plans

2001· article· en· W2024366021 on OpenAlexaboutno aff
Elizabeth Goad Oliver, Karen S. Cravens

Bibliographic record

VenueThunderbird International Business Review · 2001
Typearticle
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsnot available
Fundersnot available
KeywordsMultinational corporationSubsidiaryBusinessWelfareEmployee benefitsWarrantCompensation of employeesGovernment (linguistics)Compensation (psychology)MarketingFinanceEconomicsMarket economy

Abstract

fetched live from OpenAlex

Abstract This article describes the typical benefits offered by private and governmental employee welfare plans for 14 countries (Australia, Belgium, Canada, France, Germany, Ireland, Italy, Japan, The Netherlands, South Africa, Sweden, Switzerland, United Kingdom, and the United States). These descriptions allow managers of multinational firms to consider local employee welfare norms when establishing benefit provisions for operations outside of the home country of the multinational. Employee benefits warrant management attention due to the significant portion that benefits represent in the overall compensation package for employees, and because of the need to offer benefits that are competitive in local labor markets. Because the difficulties in managing a multinational firm are perhaps manifested most dramatically in terms of personnel, it is important to understand factors that affect providing benefits to employees. Preliminary research indicates that the cultural orientation of managers indeed has an impact on the provision of employee benefits in multinational firms. Ultimately, upper management of multinationals may need to decide between a standardized benefit package available to all subsidiaries or customized benefit programs for subsidiaries in individual countries. Managers must consider cultural norms apparent in the benefits offered by government and private entities in a local market,as well as their own cultural predilections. © 2001 John Wiley & Sons, Inc.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.816
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.057
GPT teacher head0.400
Teacher spread0.343 · 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 designTheoretical or conceptual
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

Citations8
Published2001
Admission routes1
Has abstractyes

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