Bibliographic record
Abstract
In connection with the development of society, and especially its liberalization in Western countries, differences in the standard of living of the population of different strata, age, and gender groups are being reduced. However, even in conditions of rising human living standards and scientific and technological progress, socio-economic differentiation between categories of people may still remain. The purpose of this work was to identify and determine trends in the standard of living of citizens in Canada over the past twenty years. In this regard, the work carried out a study of the income of the Canadian population in 2000–2021 in gender and age differentiation; the main trends in changes in personal income in the period under review were studied. As a result of the analysis, a significant excess of the personal income of men over the personal income of women was revealed, which decreased in the analyzed period but did not completely disappear. According to our forecasts, this difference will occur in the near future due to the presence of a higher level of pay for traditionally “male” labor. With global external liberalization in the country, traditional relations remain strong, on which economic relations are also built. The age differentiation of citizens’ incomes reflected the higher value of experience than the psychophysical properties of a person (youth, ambition, etc.). In addition, noticeable social support from the state for vulnerable segments of the population was revealed.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".