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Record W573493810

Multiculturalism and integration : Canadian and Irish experiments

2010· book· en· W573493810 on OpenAlexaboutno aff
Vera Regan, Isabella Lemée, Maeve Conrick

Bibliographic record

VenueUniversity of Ottawa Press eBooks · 2010
Typebook
Languageen
FieldSocial Sciences
TopicIrish and British Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMulticulturalismReasonable accommodationDiversity (politics)IrishIdentity (music)PoliticsSociolinguisticsSociologyCultural diversityVariety (cybernetics)Gender studiesPolitical scienceSocial scienceMedia studiesLawAestheticsLinguistics
DOInot available

Abstract

fetched live from OpenAlex

Multiculturalism and Integration provides new insights into the important issues of diversity, reasonable accommodation and identity construction in multicultural societies by examining the experiences of Canada and Ireland. While these two societies share many historical and cultural links, their differences help reveal the range of possible approaches to these important issues. Multicultural and multilingual diversity in contemporary Ireland are fairly recent phenomena, whereas Canada's policies and practices addressing cultural and linguistic diversity are several decades old. This basic difference has influenced their laws, language policies, education systems, cultural creations, and national identities as they have worked to accommodate multiculturalism. The volume brings together an international group of scholars working in a variety of fields including politics, law, sociolinguistics, literature, philosophy, and history. Their interdisciplinary approach addresses the complex factors influencing integration and multiculturalism, painting detailed and accurate portraits of these issues in Canada and Ireland.

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)0.006
metaresearch head score (Gemma)0.008
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 score0.059
Threshold uncertainty score0.266

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.004
Science and technology studies0.0130.005
Scholarly communication0.0040.001
Open science0.0020.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0070.001

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 head0.023
GPT teacher head0.246
Teacher spread0.223 · 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

Citations0
Published2010
Admission routes1
Has abstractyes

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