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Record W2601722909 · doi:10.0001/(aj).v3i12.263

Staffing Women as International Managers

2015· article· en· W2601722909 on OpenAlexaboutno aff
Binashree Hembrom

Bibliographic record

VenueANGLISTICUM. Journal of the Association for Anglo-American Studies · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicGender Diversity and Inequality
Canadian institutionsnot available
Fundersnot available
KeywordsExpatriateYardstickNOMINATEStaffingMultinational corporationDominance (genetics)BusinessPsychologyPublic relationsConstructivePopulationMarketingPolitical scienceSociologyProcess (computing)FinanceLaw

Abstract

fetched live from OpenAlex

Companies with large expatriate population most often use international assignments for early career development or training, whereas companies with fewer than 250 expatriates use them mostly to fill a senior management position. There are increasing numbers of female domestic managers, particularly in Canada and the United States, and this means more of these women candidates for foreign assignments. Many international firms want their top executives to have international experience. This implies that if women are to reach the top they need to accept expatriate assignments. Many international organisations are concerned about assigning women to countries like Japan where there is likelihood that they would not be well accepted by male counterparts. Social psychology studies explore the role of individual values in perpetuating discrimination in selection through the use of schema and stereotyping. Such studies suggest that individual selectors develop schemata of ‘ideal job-holders’ and use them as a yardstick against which all prospective candidates are measured during the process of selection. In groups where there is dominance of one gender, job-holder schemata are likely to be gender-typed. An ‘open’ system is one in which all vacancies are advertised, anyone with appropriate qualifications and experience may apply, and a ‘closed’ system is one in which selectors at corporate headquarters nominate ‘suitable’ candidates to line managers who then have the option of accepting or rejecting the offer. Keywords: Expatriate, Discrimination, Employment, Foreign assignments, Managers, Competent, International, Effectiveness, Formal/ Informal system, Open/ Closed system.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0040.002
Open science0.0000.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0150.002

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 head0.115
GPT teacher head0.364
Teacher spread0.249 · 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 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

Citations0
Published2015
Admission routes1
Has abstractyes

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