MétaCan
Menu
Back to cohort
Record W7135650424

The language and culture of Finnish immigrants and their descendants in North America

2012· dissertation· cs· W7135650424 on OpenAlexaboutno aff
Jan Chromý

Bibliographic record

VenueDigital Repository (National Repository of Grey Literature) · 2012
Typedissertation
Languagecs
FieldSocial Sciences
TopicLinguistic Variation and Morphology
Canadian institutionsnot available
Fundersnot available
KeywordsImmigrationCzechOfficial languageWork (physics)Period (music)Big Five personality traits and culture
DOInot available

Abstract

fetched live from OpenAlex

According to the statistics approximately 1,1 % of the American nation has its roots in Finland. This is mainly the consequence of mass emigration, which concerned the whole Europe during the 19th century, including Finland. Due to the conditions in their homeland, which had been absolutely unfavourable for living, thousands of Finnish citizens left for North America. In the beginning their destination was the USA, but later Canada became more desirable. There were large Finnish communities (over 30 000 people) in the states of Michigan and Minnesota in 1930 and even in 2000 thousands of Americans acknowledge Finnish ancestry. Thanks to their certain aloofness and "introvert nature" the original communities, which do not exist any more, had created a very interesting social and cultural phenomenon, of which the language was a significant part. This dialect of the Finnish language, strongly influenced by English, provides a unique chance to research the impacts of the contact of isolating English and strongly agglutinative Finnish. There is no specialized publication or even a study on this topic in the Czech language. This work aims to fill the gap at least with the basic information about the historical, cultural and mainly language development of the Finnish immigrants and their descendants in...

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)0.001
metaresearch head score (Gemma)0.001
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 score0.129
Threshold uncertainty score0.257

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0060.002
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.000
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 head0.007
GPT teacher head0.254
Teacher spread0.247 · 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

Citations0
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueDigital Repository (National Repository of Grey Literature)Same topicLinguistic Variation and MorphologyFrench-language works237,207