Negotiating borders: The ‘everyday’ encounters of Black African immigrant caregivers in Vancouver, British Columbia
Bibliographic record
Abstract
Organized around the central question of how transnational migration in a global neoliberal era has left unchallenged the gendered and racialized nature of caregiving work, my dissertation focuses on the experiences of racialized Black African immigrant caregivers in lower mainland Vancouver. In this context, my dissertation evaluates how power relations that are entrenched in social and political constructs of race, ethnicity, class, gender, immigration status etc., - as intersecting networks - administer and reinforce distinctive social inequalities, reproducing hierarchies upon which material and symbolic powers are based. Based on a life-work framework interrogating caregivers’ sense of belonging, my project identifies and discusses border encounters, as described by Black immigrant caregivers. Largely through discursive covert processes and practices, caregivers described being often singled out, and or assigned less desirable or more dangerous work. Caregivers demonstrated these border encounters through stories and narratives that epitomized their “not quite fitting in” and hence, their contradictory sense of belonging and exclusion. Indicative of the liminal experiences that often pervades the lives of racialized immigrants; these border testimonies belied the principles of a pluralistic multicultural Canada. Centered on the lives and material realities of eight respondents, this feminist ethnography was formulated through anti-racist, Black and feminist intersectional theoretical perspectives. Inspired by these theoretical foundations, the study applies the witness accounts of caregivers to explicate how they navigated isolating encounters. Through a critical re-examination of their own history, which caregivers engaged in by re-formulating social and political factors that determined their lives, my dissertation holds that this group of immigrants sought to transform their sense of selves as empowered and active agents in the work spaces they occupied. Although the caregivers employed critical approaches in negotiating contradictory encounters and resisting isolating experiences, this project finds that racialized and ethnicized social identities remained a salient theme in how the respondents interpreted and made sense of their work-related encounters. Thus, my discussion grapples with understanding how sources of, and shifts in, social identities such as race, class, ethnicity, gender etc. – as sites of (dis) empowerment – influence ‘everyday’ lived experience, and how this is negotiated and contested.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.030 | 0.009 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".