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Record W7095670639

-Draftfor discussion only Embodying Inequalities: Globalization, Health and Foreign Domestic Care Workers

2014· article· en· W7095670639 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsSolidarityHealth careGlobalizationPower (physics)Care workGlobal healthNarrativeForeign policyCapitalism
DOInot available

Abstract

fetched live from OpenAlex

Globalization has impelled high rates of labour migration from south to north. In recent years, women who migrate to work in the private households of the global north as domestics or domestic care workers comprise a large percentage of this migratory flow. In this paper, I explore the narratives of foreign domestic care workers in Canada, predominantly women from the Philippines, to uncover how forces of globalization, experiences of displacement and unequal power relations are played out and lived at the level of the body. Foreign domestic care workers often speak of diffuse bodily pains and stress, locating the etiology of their complaints in the social world. I argue that the expression of these somatic complaints can be regarded as evidence of the impact of global forces on gendered bodies and represents the embodiment of inequality. Importantly when foreign domestic care-workers share this body talk with other careworkers, they are potentially able to deploy their discourses of suffering and sacrifice to enhance social solidarity and mobilize social support. These effects, however, cannot completely mitigate their complaints especially as care-workers who remain in the country for several years begin to report declining health status concomitant with their own stalled and declining economic mobility. As it is primarily concerned with identifiable and measurable health conditions, the slipperiness of the health concerns of foreign domestic care-workers evade the gaze of a global health agenda. As a result, we fail to take into account the full range of health impacts wrought by globalization.

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)0.008
metaresearch head score (Gemma)0.018
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 score0.155
Threshold uncertainty score0.519

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.018
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0130.007
Scholarly communication0.0130.007
Open science0.0020.008
Research integrity0.0080.007
Insufficient payload (model declined to judge)0.1550.020

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 head0.015
GPT teacher head0.322
Teacher spread0.307 · 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
Published2014
Admission routes1
Has abstractyes

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