Earnings Mobility of Rural versus Urban Workers in Canada
Bibliographic record
Abstract
The policy choice to enhance household income for poor, working families depends on the dynamics of individual earnings and their direct, albeit imperfect, link to household income levels. This paper assesses the factors affecting the dynamics of low pay for rural versus nonrural individuals in Canada. Approximately one‐quarter of the rural workers sampled in Statistics Canada's SLID data receive a wage less than two‐thirds of the median wage for the period and the percentage is increasing over time. In contrast, an average of 17% of workers in urban areas receives wages below this threshold. The low pay in rural areas is also “longer lasting,” either because the probability of an upward wage move is less, because the probability of moving out of the labor force is less, or because the probability of moving down from high pay is greater. Thus, direct mechanisms such as a minimum wage are likely to be more effective in rural areas. The higher probability of a move downward (either to low pay or out of the labor force) may be associated with greater seasonal work in rural areas. Hence, policy to address rural low pay may need to take seasonality into account more than in urban labor markets.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".