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Record W2073034202 · doi:10.1515/wpsr-2012-0014

Towards a Representative Bureaucracy: Promoting Linguistic Representation and Diversity in the Swiss and Canadian Federal Public Services

2013· article· en· W2073034202 on OpenAlexaboutno aff
Daniel Kübler, Émilienne Kobelt, Stéphanie Andrey

Bibliographic record

VenueWorld Political Science · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Systems and Governance
Canadian institutionsnot available
FundersSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNational Science Foundation
KeywordsLinguistic diversityBureaucracyRationalization (economics)MultilingualismPublic servicePoliticsRepresentation (politics)Diversity (politics)Political scienceLinguisticsPublic administrationSociologyLawPedagogy

Abstract

fetched live from OpenAlex

Abstract Drawing on the concept of representative bureaucracy, this article examines how two multilingual states – Canada and Switzerland – deal with issues related to the participation of different linguistic communities in the federal public service. Following a political mobilization of the linguistic cleavage, strategies to promote multilingualism in the public service have been adopted in both countries. The Canadian strategy focuses on equal treatment of Anglophones and Francophones in the public service. In Switzerland, adequate representation of the linguistic communities is the primary goal. These differences are explained by the characteristics of the linguistic regimes in each of the two countries as well as by the peculiarities of consociational democracy in Switzerland. In both countries, the linguistic origins of public administration staff, overall, mirrors the proportions of the linguistic communities in the wider society. Within administrative units, however, linguistic diversity is hampered by the logics of language rationalization, where minorities are under pressure to communicate in the language of the majority.

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)0.013
metaresearch head score (Gemma)0.015
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.111
Threshold uncertainty score0.805

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0340.014
Scholarly communication0.0110.002
Open science0.0020.006
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.042
GPT teacher head0.341
Teacher spread0.299 · 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

Citations8
Published2013
Admission routes1
Has abstractyes

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