Employment in a post-colonial society – The case of Greenland
Bibliographic record
Abstract
In the fields of labour market research and industrial relations research, there is increasing interest in post-colonial societies and the labour market outcomes of indigenous peoples. However, existing research has generally underexplored the Greenlandic labour market. This is particularly true for factors associated with the Greenlandic Inuit population's employment outcomes. In this article, we investigate barriers and potentials for labour market participation in Greenland, focusing on individual-level factors that promote or inhibit the likelihood of being employed. We use a unique, nationally representative survey of the working-age population and explore these factors through a series of logistic regression analyses. We find that educational attainment, positive self-assessed health, and the number of people in the household were positively related to employment. Our most important findings and contributions are that respondents who answered the survey in Greenlandic were less likely to be employed compared to those who answered it in Danish. Furthermore, if a respondent was born in Greenland, compared to being born in Denmark, it lowers the likelihood of being employed. We interpret this disparity as evidence of an ethnically segregated labour market with indications of discrimination.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".