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Record W2093131144 · doi:10.1111/1471-0374.00032

Calling capital: call centre strategies in New Brunswick and New Zealand

2002· article· en· W2093131144 on OpenAlexaboutno aff
Wendy Larner

Bibliographic record

VenueGlobal Networks · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicEmotional Labor in Professions
Canadian institutionsnot available
Fundersnot available
KeywordsCall centreAgency (philosophy)Government (linguistics)IncentivePrivate sectorGlobalizationBusinessPublic sectorWageEconomic growthPublic administrationLabour economicsEconomyEconomicsPolitical scienceMarket economySociology

Abstract

fetched live from OpenAlex

This article compares government promoted call centre initiatives in New Zealand and New Brunswick, Canada, thereby identifying differing policies and practices associated with ‘globalization’. Both New Brunswick and New Zealand are small resource based economies in which policy makers aspire to attract foreign investment into call centres as a new means of economic growth and job creation. However there are significant differences between the two call centre strategies. In New Brunswick the provincial government plays a central role, most notably through the use of incentives to lure companies to the province but also through the coordination of education and training. In New Zealand an informal network made up of public and private sector actors drives the strategy, and the relevant government agency (Trade NZ) plays only a coordinating role. Despite these differences both call centre strategies aspire to link service sector activities into global flows and networks, and foster low wage and feminized forms of employment.

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 score0.080
Threshold uncertainty score0.369

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0110.008
Scholarly communication0.0080.003
Open science0.0010.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0100.001

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 head0.292
Teacher spread0.267 · 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

Citations22
Published2002
Admission routes1
Has abstractyes

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