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Record W3202155734

The Canadian-Polish Lexicon: Classes of Items and Their Semantic Distribution

2006· article· en· W3202155734 on OpenAlexaffabout
Joanna Lustański

Bibliographic record

VenuePapers from the Annual Meetings of the Atlantic Provinces Linguistic Association (PAMAPLA) · 2006
Typearticle
Languageen
FieldArts and Humanities
TopicLinguistics, Language Diversity, and Identity
Canadian institutionsYork University
Fundersnot available
KeywordsLexemeLexiconLinguisticsLexical itemVocabularyGrammarImmigrationPolishPsychologyComputer scienceHistory
DOInot available

Abstract

fetched live from OpenAlex

This paper focuses on the analysis of a specific group of lexemes used by Polish immigrants in Canada. The vocabulary used appears neither in Standard Polish nor in Standard English, but is an outcome of the contact of two separate language and culture systems and is characteristic only of the Polish language spoken by immigrant generations living outside Poland in English-speaking countries, in this case, Canada. The research reported in this paper is based on a corpus of lexeme items excerpted from a few sources: lexical and grammar surveys filled out by the respondents, the Polish media in Canada, recordings of the speech of first- and second-generation respondents, and daily conversations with Polish immigrants. On the basis of the contrastive method of language description, which also takes into consideration extralinguistic and intralinguistic factors, I distinguish seven classes of lexical items: 1. morphologically adapted lexical items, 2. structural transfers, 3. semantic transfers, 4. citations, 5. Canadian-Polish idioms, 6. caiques, 7. Canadian-Polish word-formations. A major goal of this paper is to investigate the types of Canadian-Polish lexical items and to examine the semantic distribution of these items with respect to the contact of the two cultures. This article is based on a broader sociolinguistic project examining the Polish immigrant minority group and the language spoken by this group in the Greater Toronto Area (GTA) (Lustanski 2005).

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)0.001
metaresearch head score (Gemma)0.023
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.427
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
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 head0.006
GPT teacher head0.179
Teacher spread0.173 · 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 designObservational
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
Published2006
Admission routes2
Has abstractyes

Explore more

Same venuePapers from the Annual Meetings of the Atlantic Provinces Linguistic Association (PAMAPLA)Same topicLinguistics, Language Diversity, and IdentityFrench-language works237,207