IMMIGRANT EMPLOYMENT INTEGRATION IN A MID-SIZED CITY
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Canada relies on immigration to drive population and economic growth. It ranks as a top destination for international migrants worldwide with some of the most highly educated, highly skilled immigrants entering the country each year. Yet, evidence suggests that recent immigrants perform poorly in the labour market when compared to their Canadian-born counterparts. Where immigrants settle can impact on how they effectively integrate into employment. Regionalization policies have resulted in a larger share of immigrants settling in small and mid-sized cities across the country. This dissertation examines the employment integration of recent immigrants to the mid-sized city of Guelph, Ontario. It uses a systems approach to map the connection between immigrant services and the local labour market and provides a descriptive analysis of immigrants’ early experiences on the pathway to employment. As the immigrant population grows, cities will face the greatest pressures to facilitate the effective and efficient employment integration of immigrants.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.045 | 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 it