The role of knowledge in the integration experience of Ethiopian immigrants to Toronto
Bibliographic record
Abstract
Migration of populations involves not merely physical transplantation but often a movement from one framework of knowledge to another. The decision to migrate is often based on the recognition of imminent threats at the present location or better opportunities elsewhere. Hence, migrants do not leave their countries with blank slates nor do they flow in certain directions without some knowledge to guide their journeys. In this thesis, the preeminence of knowledge in facilitating migratory transitions is investigated through multiple methods (census data, document analysis, interviews and a survey). The qualitative and quantitative methods used allow a concurrent examination of the roles of indigenous and western knowledge in the migratory experience of Ethiopian immigrants to Toronto. The findings that emerged from the study discern that these two knowledge systems interact both in consensual and confrontational styles--the dual styles further integrative knowledge acquisition in different fashions. (1) While indigenous knowledge stabilizes immigrants' psychological states, Western knowledge facilitates life-sustaining material acquisition. In other words, while indigenous knowledge serves to explain emotional salience, Western knowledge serves to explain epistemic salience in the lives of immigrants. (2) Knowledge age integration is a personal and processional. Immigrants' pace of integration is dependent on their capacities to perform in various domains, such as employment, housing and education. The study shows that the concurrent utilization of indigenous and host knowledge systems facilitates integration. This research approaches both systems of knowledge as a fluid mixture of experiences, values, contextual information and insights. They both provide a framework for evaluating and incorporating new experiences. Both indigenous and host society knowledge is embedded not only in documents but also in social routines, processes, practices and norms, guiding migrants throughout the phases of migration.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.007 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".