Imagining Winnipeg: The translocal meaning making of Filipino migrants to Canada
Bibliographic record
Abstract
This study examines how, in the words of Appadurai, “locality emerges in a global world” (Appadurai, 1996, p.18). Specifically, it articulates the nature of information practices in the lives of 14 newcomers to Canada who have migrated from the Philippines to the medium‐size city of Winnipeg. Using a qualitative and exploratory approach, this study applies a transnational lens to this area of research to make explicit the detailed activities and outcomes of newcomer information practices, in particular drawing out the dimensions and implications of newcomers' participation within and across local and global social networks, translocal information landscapes, and across their settlement trajectories. The result is a Translocal Meaning Making process that describes how newcomers come to make sense and use information across distinct and sometimes contradictory information spaces. Our findings suggest that migrant information practices shift across space and time and are constituted both individually, through cognitive and affective processes, and socially, through shared imaginaries, through interactions within and across translocal information landscapes, and through complex deterritorialized networks of people and resources.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.027 | 0.019 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| 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".