Projecting the immigrant population of Norway
Why this work is in the frame
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Bibliographic record
Abstract
The sharply increasing immigration to Western Europe in recent years has been accompanied by a growing interest in the size and composition of the future number of immigrants. This interest is based on reasons ranging from racism, xenophobia and other reasons for opposing immigration, to concerns about the integration of immigrants into society and the effects of immigration on the economy. Attempts to project the population of immigrants face a number of challenges such as ethical issues, definition of immigrants, modelling, data needs and as-sumptions about future migration flows, fertility behaviour, etc. This paper presents the choices made on some of these issues in the projection of the immigrant population of Nor-way. Projections of immigrants or other ethnic or minority populations have also been made in sev-eral other countries, including Denmark, The Netherlands, Sweden and Austria. Definitions and methodology vary and depend partly on the issues of interest but also on the data avail-ability. Countries with good administrative registers, such as the Nordic countries and The Netherlands, have focused on data that are available in the registers, such as country of origin or birth. In other countries projections have been made by ethnicity/race (USA and Canada) and religion (Austria). Statistics Norway has made projections of the immigrant population in 2005 and 2008 and will publish a new set in June 2009. The immigrant population is defined by country of birth. Persons born in Norway of parents born abroad have also been included. This paper presents the methodology, data and major projection results. We found that the most sensitive factor in the projections is the assumption about the future net immigration. We have, therefore, estimated an economic model of migration to Norway, which is presented here. Finally, we will discuss possible future extensions of the model.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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