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Record W4200125357 · doi:10.1111/1748-8583.12422

International human resource management in multinational companies: Global norm making within strategic action fields

2021· article· en· W4200125357 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 · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Student and Expatriate Challenges
Canadian institutionsUniversité de MontréalMontreal Council on Foreign Relations
FundersEconomic and Social Research Council
KeywordsMultinational corporationNorm (philosophy)Human resource managementBusinessHuman resourcesPosition (finance)Knowledge managementGlobal strategyAction (physics)Work (physics)Industrial organizationEconomic systemProcess managementPolitical scienceManagementMarketingEconomicsEngineeringComputer science

Abstract

fetched live from OpenAlex

Abstract The formation of global norms that affect work is a crucial element to how multinational companies (MNCs) achieve a degree of HR integration internationally. We establish a ‘strategic action fields’ framework to guide research into global norm‐making in MNCs in general and for analysing the work of those that we term ‘globalising actors’—those who are active in globalising a firm's management of its human resources—in particular. We position our framework with relation to existing research in international human resource management, and show how the field can benefit from achieving an approach to global norm‐making that is contextualised, personalised and contested.

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient 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 score0.900
Threshold uncertainty score1.000

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 studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.095
GPT teacher head0.394
Teacher spread0.299 · 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