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Record W2150326550 · doi:10.1080/09585192.2012.668391

To what extent is there a regional logic in the management of labour in multinational companies? Evidence from Europe and North America

2012· article· en· W2150326550 on OpenAlexaffabout
Tony Edwards, Patrice Jalette, Olga Tregaskis

Bibliographic record

VenueThe International Journal of Human Resource Management · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Student and Expatriate Challenges
Canadian institutionsUniversité de MontréalMontreal Council on Foreign Relations
FundersEconomic and Social Research Council
KeywordsMultinational corporationContext (archaeology)Regional scienceVariation (astronomy)Scale (ratio)Economic geographySimilarity (geometry)Social network analysisRegional studiesComparative researchPolitical scienceSociologyEconomyRegional developmentGeographyEconomicsSocial science

Abstract

fetched live from OpenAlex

Abstract This paper questions the extent to which a regional logic is adopted by multinationals in how they organise their operations overseas, and seeks to examine the variation within and across regions in this regard. Data are drawn from two of the parallel surveys of employment practice undertaken by the INTREPID (is a research network of academics across 10 countries engaged in comparative research on multinationals) network, namely Canada and the UK. The analysis tests four hypotheses regarding the similarity and differences in the adoption of a regional logic using the data as illustrative of firms in the regions of North American and European. Our analysis demonstrates how divergent structures and dynamics of regional integration in different continents have led to different strategies and processes in multinational companies. In doing so the paper provides insights into the nature of variation within the multinational community and across regional contexts. Keywords: HRMinternational managementmultinationalsregional structures Acknowledgements This article draws on data from a large-scale survey on 'Employment Practices in Multinationals in Organisational Context'. This study was funded by the UK Economic and Social Research Council (award numbers RES-000-23-0305 and RES-062-23-2080) and in Canada by the Social Science Research Council. Notes †Current address: University of East Anglia, Norwich, UK.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.584
Threshold uncertainty score0.299

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.082
GPT teacher head0.352
Teacher spread0.270 · 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 designQualitative
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

Citations15
Published2012
Admission routes2
Has abstractyes

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