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Human Resource Management in the Anglo-Saxon Countries

2021· book-chapter· en· W3156255231 on OpenAlexaff
Geoffrey Wood, Chris Brewster

Bibliographic record

VenueOxford University Press eBooks · 2021
Typebook-chapter
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsWestern University
Fundersnot available
KeywordsProperty rightsIndividualismCapitalismInsiderGovernment (linguistics)Human rightsPoliticsPolitical scienceCorporate governanceOligopolyPrivate propertyPolitical economyLaw and economicsMarket economyEconomicsLawManagement

Abstract

fetched live from OpenAlex

Abstract The Anglo-Saxon countries or the liberal market economies are just about the only example of a country grouping that both the cultural theories and the comparative institutional theories agree on. Culturally, these countries are characterized by low power distance, high individualism, and low uncertainty avoidance. Institutionally, these countries have shared legal origins (common law) and specific political systems (first-past-the-post in most instances). They are the stock market capitalist, liberal market, or compartmentalized capitalist countries. They are characterized by powerful private property rights, lesser rights for other stakeholders, and government being less interested in supporting stakeholder rights, with commensurate suspicion of government involvement (other than in respect of bailouts of politically connected insider corporations) and taxation. Competition is depicted as unalloyed good, even if in practice such markets are often characterized by powerful oligopolies. This is important because the original theories of management and of human resource management, most of the research, and much of the current thinking in these areas come from the United States of America; most of the largest management consultancies have their headquarters or draw their inspiration from the United States; and academic teaching and publication follow the United States. There have, however, been debates about how cohesive and consistent the Anglo-Saxon category is and precisely how the implications for human resource management are manifested in each country.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.026
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.024
GPT teacher head0.189
Teacher spread0.165 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2021
Admission routes1
Has abstractyes

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