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Record W4406043636 · doi:10.1515/9781474491648

New Gaelic Speakers in Nova Scotia and Scotland

2024· book· en· W4406043636 on OpenAlexaboutno aff
Stuart Dunmore

Bibliographic record

VenueEdinburgh University Press eBooks · 2024
Typebook
Languageen
FieldArts and Humanities
TopicScottish History and National Identity
Canadian institutionsnot available
Fundersnot available
KeywordsNova scotiaNova (rocket)HistoryGeographyEthnologyEngineeringAeronautics

Abstract

fetched live from OpenAlex

Exploring the motivations, practices and ethnolinguistic identities of new Gaelic speakers Outlines the history of Gaelic language use in Scotland and Nova Scotia, juxtaposing its historical decline with contemporary revitalisation efforts in both territories Situates the discrete settings of Gaelic communities in Scotland and Nova Scotia with rich ethnographic portrayals Employs quantitative and qualitative analyses to examine Scottish and Nova Scotian ‘new’ Gaelic speakers’ language practices and the motivational factors underlying these practices What are the main similarities between new cohorts of Gaelic speakers in Nova Scotia and Scotland, and what key differences distinguish them? In Scotland, public policy to support and maintain the language has increased substantially in the past 40 years. In addition to Scotland’s 57,602 speakers, however, Gaelic has persisted in Nova Scotia since the 18th century and a third of Nova Scotians are descended from families who spoke the language historically. As a response to policymakers’ language planning priorities in both polities and drawing on three years of ethnographic research in Scotland and Nova Scotia, this book presents a comparative analysis of new speaker motivations, identities and linguistic ideologies. An innovative approach to examining bilingual discourses is employed to demonstrate key distinctions and commonalities among new Gaelic speakers, with a view to informing future policy to generate greater numbers of proficient speakers on both sides of the Atlantic.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.302
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.032
GPT teacher head0.206
Teacher spread0.174 · 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.

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

Citations1
Published2024
Admission routes1
Has abstractyes

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