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Record W2504782960

Discourses of belonging and resistance: Irish-language maintenance in Ireland and the diaspora

2014· dissertation· en· W2504782960 on OpenAlexaboutno aff
Jill Vaughan

Bibliographic record

VenueMinerva Access (University of Melbourne) · 2014
Typedissertation
Languageen
FieldSocial Sciences
TopicResearch in Social Sciences
Canadian institutionsnot available
Fundersnot available
KeywordsDiasporaIrishResistance (ecology)LinguisticsHistorySociologyGenealogyAnthropologyGender studiesPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

Almost 2 million people in the North and South of Ireland identify as Irish speakers and an estimated 70 million around the globe can claim Irish heritage. While Irish ancestry may be distant for many, the Irish language is active in numerous diasporic communities, as documented in some limited research (e.g. Ihde 1994, Ó hEadhra 1998, Noone 2012a) and evidenced by the existence of cultural and language groups. Census figures indicate that over 30,000 people currently speak the language in Canada, the United States and Australia alone, yet no general account of Irish-language use in the diaspora exists. Linguistic practices within Irish communities worldwide vary widely with regard to Irish-language use, with each community subject to distinct concerns, histories and discourses. As such each has different possibilities for creating social meaning through language use. The aim of this thesis is: (i) to explore Irish-language learners’ and speakers’ characterisations of patterns of language use and language-community formations between sites in the Republic and Northern Ireland (chiefly Galway, Dublin, Derry and Belfast) and in the diaspora (Melbourne, Australia; Boston, U.S.; and St. John’s, Newfoundland, Canada); and (ii) to examine the (Foucauldian) discourses within which Irish-language use is implicated as a meaningful social practice within and across these communities. Research is based on open-ended qualitative interviews with 86 learners and speakers regarding the Irish language and their own language practices, and in extensive participant observation of cultural and language-related activities in each site. Thematic content analysis of interview data provides the basis for ethnographic descriptions of each site. Foucauldian discourse analysis is used to discover and delineate the predominant discourses (and counter-discourses) within which Irish-language use is implicated as a meaningful social act, and that are enacted or actively resisted within and across communities, as well as key subject positions made available within these discourses. The research predominantly targets learners and teachers of Irish, and those involved in language maintenance in each of these communities, and focuses particularly on elective bilinguals – speakers who have learnt Irish in the classroom and who do not use Irish as their primary language. The focus on this kind of bilingual speaker is of paramount importance for two reasons: firstly, because attitudinal research has been largely silent on elective Irish bilinguals, and secondly, because elective bilinguals are likely to be crucial to the language’s survival. Patterns of bilingualism in Gaeltacht regions are shifting and changing, and, as such, circumstantial bilinguals make up decreasing proportions of the language’s speaker community. Urban language communities (largely made up of L2 speakers), however, are increasing in size and activity. This thesis argues for an incorporation of post-structuralist, social constructionist approaches to identity within sociology of language, particularly with regards to elective bilinguals and in diasporic contexts. As such, in addition to contributing to a broader description of Irish-language communities worldwide, this thesis demonstrates the contributions that a critical discourse analytic approach can make in endeavouring to understand the changing position of linguistic minorities in post-modernity.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.237
Threshold uncertainty score0.934

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.017
GPT teacher head0.329
Teacher spread0.312 · 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.

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

Citations0
Published2014
Admission routes1
Has abstractyes

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