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Record W4383459355 · doi:10.1515/9780773598515

Creating Kashubia

2016· book-chapter· en· W4383459355 on OpenAlexaboutno aff
Joshua C. Blank

Bibliographic record

VenueMcGill-Queen's University Press eBooks · 2016
Typebook-chapter
Languageen
FieldSocial Sciences
TopicHistorical Geopolitical and Social Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsGeography

Abstract

fetched live from OpenAlex

In recent years, over one million Canadians have claimed Polish heritage - a significant population increase since the first group of Poles came from Prussian-occupied Poland and settled in Wilno, Ontario, west of Ottawa in 1858. For over a century, descendants from this community thought of themselves as Polish, but this began to change in the 1980s due to the work of a descendant priest who emphasized the community’s origins in Poland’s Kashubia region. What resulted was the reinvention of ethnicity concurrent with a similar movement in northern Poland. Creating Kashubia chronicles more than one hundred and fifty years of history, identity, and memory and challenges the historiography of migration and settlement in the region. For decades, authors from outside Wilno, as well as community insiders, have written histories without using the other’s stores of knowledge. Joshua Blank combines primary archival material and oral history with national narratives and a rich secondary literature to reimagine the period. He examines the socio-political and religious forces in Prussia, delves into the world of emigrant recruitment, and analyzes the trans-Atlantic voyage. In doing so, Blank challenges old narratives and traces the refashioning of the community’s ethnic identity from Polish to Kashubian. An illuminating study, Creating Kashubia shows how changing identities and the politics of ethnic memory are locally situated yet transnationally influenced.

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)0.004
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.028
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0280.009
Scholarly communication0.0100.011
Open science0.0020.025
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0240.005

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 head0.018
GPT teacher head0.230
Teacher spread0.212 · 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 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

Citations2
Published2016
Admission routes1
Has abstractyes

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