Demographic Structure, Intersecting Identities, and Employment Inequalities
Bibliographic record
Abstract
This study seeks to understand the role of demographic structure of the society as it pertains to the group size (i.e., number of group members) and individuals’ intersecting identities in shaping employment inequalities. Integrating homophily, intersectionality, and theory of minority group threat, we examine the likelihood of employment and level of employment income of individuals with varying immigrant and disability statuses. Our data consists of three Statistics Canada datasets: the 2001 and 2006 waves of the Participation and Activity Limitation Survey (PALS) linked with the 2001 and 2006 Censuses, and the 2012 Canadian Survey on Disability (CSD) linked with the 2011 National Household Survey 2011. We conduct our analysis by examining the following sub-groups: Canadian-born with no disabilities (CnD), immigrants with no disabilities (InD), Canadian-born with disabilities (CwD), and immigrants with disabilities (IwD). Consistent with the theory of minority group threat and intersectionality, we find that IwD benefit from being the smallest sub-group. Furthermore, the positive impact of being IwD on employment inequalities is limited by the homophilious employment patterns demonstrated by the consistent employment inequalities favoring CnD. Overall, our findings demonstrate that homophily, intersecting identities, and group size at the societal level shape employment inequalities at varying degrees and directions.
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 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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".