Gendered Citizenship: A Case Study of Paid Filipino Male Live-In Caregivers in Toronto
Bibliographic record
Abstract
Nation-states tend to be coded as feminine, "the motherlands" that procreate citizens.In Italy, Africa is a single trope of the female body (Carter 1997) where African women migrants have been popularly classified as prostitutes, those who sell themselves and are resold as commodities, and as the most expendable of all human populations, the most easily exploited (Merill 2011: 1559) ABSTRACTPhilippines is considered as a major provider of caregiving services in Canada.Caregiving has historically been identified as feminine labour.As such, providing paid caregiving has always been associated with immigrant women.Policies are thus built to control this work and mostly they tie with the masculine culture of the society.In Canada, live-in caregiving is very gendered and masculine, and as such it discriminated men of colour.This paper is focused on a case study that was done in 2014 in Toronto.There were three paid Filipino male live-in caregivers who participated in this study.The study applied qualitative narrative research methodology.The purpose of this article is to discuss and analyse the participants' experiences and understand how Canadian hegemonic and imperial IJAPS, Vol. 13, No. 1, 51-71, 2017 Gendered Citizenship 52 masculinity shapes citizenship and policy in a racialised and gendered manner.Within this argument, we explore in the introduction of this article the discourse of masculinity.We also look at the history of Live-in Caregiver Program in Canada.Additionally, we deliberate and examine the participants' narratives on gendered citizenship, gendered policy, and the nature of their job.The conclusion is based on the narratives of the Filipino male live-in caregivers and their discrimination in caregiving work on the basis of their citizenship and masculinity.The conclusion also looks at how they are able to negotiate their salary, their time to work, and how they work with their clients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.024 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".