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Record W2594492314 · doi:10.29173/md28573

Differences and Similarities in Attitudes towards Intellectual and Visual Culture within the Ukrainian-Canadian Community in Edmonton, Alberta

2016· article· en· W2594492314 on OpenAlex
Susanna M. Lynn

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueMultilingual Discourses · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsUniversity of Alberta
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsUkrainianEthnic groupSalientIdentity (music)Independence (probability theory)SociologyCultural group selectionPsychologySocial psychologyGender studiesLinguisticsPolitical scienceAnthropologyAestheticsLaw

Abstract

fetched live from OpenAlex

Ukrainian-Canadians are a relatively well-established group in Canada. This paper draws on data gathered from ten interviews about ethnic identity discourses which I conducted with new and established members of the Ukrainian-Canadian community in Edmonton, Alberta. Using critical discourse analysis, I investigate the responses to nine of the original thirty-seven interview questions, which included two ranking questions; these questions inquired about participants’ opinions and evaluations of [Ukrainian] literature, language, music and important “kinds” and aspects of culture. Responses exposed some of the similarities and differences in attitudes the two groups held towards intellectual and visual culture, highlighting the evolving nature of this community, and providing detail that enhances understanding of these attitudes. I present key arguments as to why these similarities and differences may, at least in part, correlate to the unique socio-cultural environments in which each group has been developing culture since Ukraine’s Independence. In particular, I posit that “the linguistic factor” (a term I use to summarize the interconnected influence that language, literature, and linguistic ability have on each other) is one of the most salient forces in shaping and informing these similarities and differences in attitudes towards intellectual and visual culture.

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.

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)0.001
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation 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 score0.466
Threshold uncertainty score0.612

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.075
GPT teacher head0.432
Teacher spread0.357 · 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