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Record W2139261797 · doi:10.2307/541278

Looking Through My Mother’s Eyes: Life Stories of Nine Italian Immigrant Women in Canada

2000· article· en· W2139261797 on OpenAlexaboutno aff
John Allan Cicala

Bibliographic record

VenueJournal of American Folklore · 2000
Typearticle
Languageen
FieldArts and Humanities
TopicFolklore, Mythology, and Literature Studies
Canadian institutionsnot available
Fundersnot available
KeywordsFolkloreIconImmigrationCitationFolklifePublishingHistoryDownloadLibrary scienceArtLiteratureWorld Wide WebComputer science

Abstract

fetched live from OpenAlex

Book Review| January 01 2000 Looking Through My Mother’s Eyes: Life Stories of Nine Italian Immigrant Women in Canada Looking Through My Mother’s Eyes: Life Stories of Nine Italian Immigrant Women in Canada, Giovanna Del Negro. John Allan Cicala John Allan Cicala Search for other works by this author on: This Site Google Journal of American Folklore (2000) 113 (447): 107–108. https://doi.org/10.2307/541278 Cite Icon Cite Share Icon Share Facebook Twitter LinkedIn Email Permissions Search Site Citation John Allan Cicala; Looking Through My Mother’s Eyes: Life Stories of Nine Italian Immigrant Women in Canada. Journal of American Folklore 1 January 2000; 113 (447): 107–108. doi: https://doi.org/10.2307/541278 Download citation file: Zotero Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All Scholarly Publishing CollectiveUniversity of Illinois PressJournal of American Folklore Search Advanced Search The text of this article is only available as a PDF. Copyright 1999 The American Folklore Society1999 Article PDF first page preview Close Modal You do not currently have access to this content.

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)0.002
metaresearch head score (Gemma)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.207
Threshold uncertainty score0.416

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.006
Science and technology studies0.0050.002
Scholarly communication0.0040.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.011
GPT teacher head0.226
Teacher spread0.215 · 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

Citations6
Published2000
Admission routes1
Has abstractyes

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