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Record W3032971020

The Complex Families of Filipina Immigrant Nurses and Garment Workers in Manitoba in the Sixties

2018· article· en· W3032971020 on OpenAlexaboutno aff
Jeden O. Tolentino

Bibliographic record

VenueCrossings · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsImmigrationNormativeSiblingEthnic groupSociologyGender studiesGenealogyGeographyPolitical scienceHistoryAnthropologyLawArchaeology
DOInot available

Abstract

fetched live from OpenAlex

This paper adds to the critique of the thesis that the nuclear family was normative in Western society by describing the “complex” families that Filipina nurses and garment workers built when they immigrated to Manitoba in the 1960s. Upon their arrival in Manitoba, these Filipinas formed substitute sibling families that served as natural support systems. Then, after having settled in the province, they took on parental roles toward the kin they had left behind in the Philippines as well as fellow Filipinos who had immigrated to Canada after them. Finally, they sponsored close relatives to join them in Manitoba when Canadian immigration policy became more open. However, the socio-economic stratification within the Filipino community in Manitoba during its first decade in the province affected the ways nurses (among other professionals) and garment workers (among other working-class individuals) respectively built these “complex” families from different perspectives and with different approaches.

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)0.002
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 score0.055
Threshold uncertainty score0.253

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0270.008
Scholarly communication0.0030.001
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.021
GPT teacher head0.273
Teacher spread0.251 · 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
Published2018
Admission routes1
Has abstractyes

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