Longitudinal Survey of Immigrants to Canada: progress and challenges of new immigrants in the workforce 2003
Bibliographic record
Abstract
This release contains the first results from the second wave of the Longitudinal Survey of Immigrants to Canada (LSIC). The LSIC was designed to study how new immigrants adjust over time to living in Canada. Results from the first wave of the LSIC1 showed that labour market integration is a particularly critical aspect of the immigrant settlement process. This release therefore focuses on this issue. The release addresses questions such as: how long does it take new immigrants to get their first job? How many of them find employment in their intended occupation? And what obstacles do they encounter when looking for work? Given the focus on labour market integration, the analysis is limited to the 6,000 immigrants who were in the prime working-age group of 25 to 44 years, representing 106,600 people. Moreover, particular emphasis is placed on principal applicants in the skilled worker category, since these individuals are admitted to Canada because of their high level of labour market skills. Finally, labour market integration is examined over the first two years in Canada, broadly defined as the 24 to 28 months between landing and the time of the second LSIC interview. The vast majority (80%) of prime working-age immigrants found employment during their first two years in Canada, and most worked for more than one year. Of those who found employment, 42% obtained a job in their intended occupation. This was the case for about half (48%) of principal applicants in the skilled worker category.
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.
How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".