Navigating Waters: Experiences of Filipino Canadian Identity Making in the Diaspora
Bibliographic record
Abstract
Research states that while Filipino Canadians are the largest growing migrant population in Canada, they are the least represented and understudied subjects in the academy. The primary purpose of this qualitative study is to better understand the experiences of Filipino Canadians and how they create their identities in the diaspora. Since few studies take on a social work lens to explore these important stories, I attempt to unearth these experiences using these guiding questions: (1) How do Filipino Canadians integrate their cultural identity in the diaspora? (2) What are the sociopolitical and historical conditions that inform these identities? Following Charmaz’s Constructivist Grounded Theory, data were generated from ten (10) Filipino Canadians across Vancouver, British Columbia and analyzed using codes, categories and turning them into themes. Six themes were found. Findings indicate that Filipino Canadians yearn to construct, deconstruct, and reconstructing identities that bring them back to their cultural and ancestral roots. Implications for social work practice and lessons are discussed.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.054 | 0.017 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".