Unequal Inequality: The Distribution of Individuals' Earnings by Province *
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Bibliographic record
Abstract
Abstracts: Unequal Inequality: The Distribution of Individuals' Earnings by Province. This paper presents the results of an empirical analysis of earnings at the provincial level based on the recently available Longitudinal Administrative Database. The paper addresses the following questions: Are there significant differences in earnings by province? What are the patterns of any such differences, such as along regional lines or with respect to income levels? Were there any important shifts in the level of at the national level or in the patterns by province over the 1982-94 period covered by the analysis? Do the provincial patterns change when is measured using earnings averaged over several years--that is, taking earnings mobility into account--or when other income measures are employed, such as when self-employment, professional, or investment income, or government transfers, are included, or when taxes are deducted? Entrenched in the Canadian political-economi c-social psyche is the notion of and provinces, but the results reported here should allow us to now also speak in terms of inequality and less inequality provinces. Policy implications are discussed. ********** Thanks to a substantial accumulation of research, we now know a good deal about earnings in Canada in terms of its overall level, the sub-group patterns (e.g., by age, sex and level of education), and the shifts which have occurred over time.' There is, however, one area in which our understanding is virtually nil: earnings at the provincial level. (2) The contribution of this paper is to report the results of an empirical analysis of earnings at the provincial level over the 1982-1994 period based on the recently available Longitudinal Administrative Database. The paper addresses the following questions: * Were there significant differences in earnings by province over this period? If so, were there any clear tendencies along regional lines or any other provincial characteristics, such as industrial base or income levels (i.e., the richer versus poorer provinces)? * Were the patterns consistent across age-sex groups? For example, in provinces where there was greater among men, were women's earnings also more unequally distributed? Related to this, were the provincial differences at the aggregate level due to common patterns across all age-sex groups or due to composition (i.e., different proportions of lower/higher age-sex groups across the provinces)? * Were there any significant shifts in earnings at the national level or in the provincial patterns over the period covered by the analysis? In particular, was there convergence (with reductions in in the high provinces and increases in the low provinces), increased divergence, or were the changes more idiosyncratic than to allow for such broad characterisations? * Do the patterns change when is measured using earnings averaged over several years at the individual level--that is, taking earnings mobility into account? * What are the patterns when other income measures are considered, such as when other sources of market income and transfers are included, or when taxes are subtracted out? The results presented here thus provide an empirical view of labour market outcomes at the provincial level which should add to our general understanding of work and pay in Canada and also provide evidence on the effects of adding other income sources and taxes to the distribution of final incomes in each province. The paper thus furnishes new information on the regional nature of labour markets in Canada, a topic addressed at the international level in OECD (2000). Furthermore, this comes in a context where it is not obvious what the expected patterns would be. …
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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 | 0.002 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it