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Record W4404823034 · doi:10.4324/9781003036425-4

Labor here, consume there, accumulate everywhere

2024· book-chapter· en· W4404823034 on OpenAlexaboutno aff
Pauline Gardiner Barber, Catherine Bryan

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicDigital Economy and Work Transformation
Canadian institutionsnot available
Fundersnot available
KeywordsAlmost everywhereEconomicsHistoryMathematics

Abstract

fetched live from OpenAlex

Probing beyond statistics, Barber and Bryan’s chapter examines the improvisations of capital and labor along the Philippines–Canada migration corridor. With reference to ethnographic cases coinciding with the feminization of Philippine labor export in the 1980s and the restructuring of Canada’s immigration system since 2008, the chapter explores the experiences over time of many well-qualified migrants arriving in Canada as temporary workers traveling under different visa programs where increasingly well-educated women predominate. Many well-educated Filipinos drawn to Canadian futures have sought transfer to permanency through targeted federal and/or provincial immigration programs described here. The authors argue that the social reproduction of Philippine migration can be linked to women’s social reproductive labor in the care sector and later in healthcare and food services, where migrant contributions to mobile capital as workers in Canada and consumers in the Philippines, in one global food service corporation, well illustrates the social reproduction of Philippine migration with its anchoring in feminized migration. The chapter concludes with a brief mention of how the COVID pandemic exposed the continuing vulnerability of Philippine migrant workers despite their major contributions to the nation’s economy and to the countries where their labor services the accumulation projects of internationally mobile capital.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.746
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0110.011

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 head0.028
GPT teacher head0.278
Teacher spread0.250 · 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; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
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

Citations0
Published2024
Admission routes1
Has abstractyes

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