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Record W2953963934 · doi:10.15760/etd.6716

A Cross-national Study of Attitudes and Group Labeling: Multinational Corporation (MNC) Workers in Canada, Brazil, and West Germany

2000· report· en· W2953963934 on OpenAlexaboutno aff
Tobias Eyck

Bibliographic record

Venuenot available
Typereport
Languageen
FieldSocial Sciences
TopicSocial and Educational Sciences
Canadian institutionsnot available
Fundersnot available
KeywordsMultinational corporationContext (archaeology)PoliticsMeaning (existential)BusinessPolitical scienceCorporationSociologyEconomic geographyGeographyPsychology

Abstract

fetched live from OpenAlex

Many studies concerning multinational corporations (MNCs) are replete with theoretical models and case studies that treat MNCs as stand-alone entities. Very little time and effort is given to understanding the context in which MNCs operate. This context includes not only the fact that MNCs transcend national boundaries (political as well as geographical), but also the meaning of work and being part of a multinational work force for those employed within MNCs. This thesis is an effort to elucidate how the political/societal/cultural contexts of different host countries affect the attitudes of those workers most directly involved with foreign-owned MNCs. By shifting the focus from the MNC to the political/societal/cultural environment of host countries, foreign-owned MNCs can be compared across national boundaries (foreign-owned MNC workers from three different countries are compared in this thesis -- Canada, Brazil, and West Germany). Finally, by grounding the workers' attitudes within social identity theory, divergent attitudes between the workers from the different countries are not only explained, but expected as well.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.992

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 science0.0000.000
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 head0.061
GPT teacher head0.400
Teacher spread0.339 · 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 designObservational
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
Published2000
Admission routes1
Has abstractyes

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