Harmonising migration : an analysis of points based systems adapting the best practices from Canada, Australia, and the UK for a unified European Union immigration framework
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This thesis delves into the intricate landscape of immigration policies, specifically focusing on the Points Based Systems (PBS) employed by Canada, Australia, and the United Kingdom. Each of these countries has pioneered unique PBS mechanisms, reflecting their socio-economic needs and migration objectives and I hope that by dissecting the strengths and disadvantages of each system it will be possible to extract the best practices and potential pitfalls. The ultimate aim is to utilise these insights into a proposal for a unified European Union Points Based immigration system. I will attempt to comparatively analyse these three systems, while drawing parallels and contrasts between distinct national contexts and the diverse socio-political landscape of the EU, aspiring to provide a roadmap for EU policymakers. By combining the advantages of established systems and circumventing the identified challenges, the envisioned EU PBS seeks to foster efficient, equitable and strategic immigration policies that align with the EU’s broader objectives and values, in the light of articles 79 and 80 of the TFEU.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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