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Multiculturalism in Business

2015· other· en· W2519120839 on OpenAlexaff
Mary Yoko Brannen

Bibliographic record

VenueThe Wiley Blackwell Encyclopedia of Race, Ethnicity, and Nationalism · 2015
Typeother
Languageen
FieldSocial Sciences
TopicInternational Student and Expatriate Challenges
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsMulticulturalismMelting potSociologyCultural assimilationImmigrationNorm (philosophy)Diversity (politics)Assimilation (phonology)Value (mathematics)Cultural diversityCultural pluralismTerm (time)Gender studiesSocial scienceEpistemologyEthnic groupLinguisticsAnthropologyPolitical scienceMathematicsLawPedagogyPhilosophy

Abstract

fetched live from OpenAlex

Multiculturalism is a term used both descriptively and prescriptively. It is used descriptively in reference to the cultural diversity of communities with a significant proportion of people with mixed cultural origins. It may describe the demographic makeup of an entire state or that of an organization such as a business, school, city, or neighborhood. Prescriptively, the term relates to principles and policies that value diversity and is inclusive of cultural variation in language, religion, dress, values, and basic assumptions about life. In terms of integration, multiculturalism is contrasted to assimilation and the expectation that immigrant groups should adapt to the cultural norm. Whereas assimilated communities are often described as “melting pots” or “salad bowls,” the term “cultural mosaic” is more apt to be used in reference to multiculturalism. The terms “bicultural” and “multicultural” are regularly used to describe individuals who have been deeply socialized in two or more cultures.

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)0.003
metaresearch head score (Gemma)0.003
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: Other
Teacher disagreement score0.014
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0140.023
Scholarly communication0.0110.005
Open science0.0010.011
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0080.001

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 head0.025
GPT teacher head0.317
Teacher spread0.292 · 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

Citations5
Published2015
Admission routes1
Has abstractyes

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