“So many things were new to us”: identifying the settlement information practices of newcomers to Canada across the settlement process
Bibliographic record
Abstract
Purpose The purpose of this paper is to identify and map the shifting relationship between the settlement process and the information practices of newcomers from the Philippines as they migrate and settle in Canada. Design/methodology/approach This research employs two semi-structured in-depth interviews, each with 14 newcomers from the Philippines to Canada. Participants were selected because they had migrated to Winnipeg through the Manitoba Provincial Nominee Program within 1–4 years of the date of interview. Findings Eight settlement information tables are identified that demonstrate participants' migration experiences, including participants' thoughts and feelings related to migration and settlement, their information questions and needs, the information resources they consult and the activities in which they engage. Originality/value This paper argues that this phased model approach documents the shifting relationship between settlement processes and migrants' information needs, activities, resources and practices. Articulating study findings using this phased model approach can support information institutions, such as the settlement sector and libraries, to provide support to newcomer groups in a timely and targeted manner.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.020 | 0.010 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".