What is Wrong with Methodological Nationalism? An Argument About Discrimination
Bibliographic record
Abstract
Abstract Methodological nationalism is a cognitive bias that construes states as the natural and necessary form of contemporary social organisation. This gives rise to a state-centred view which naturalises national communities, exaggerates the differences between citizens and migrants, and exceptionalises international migration. In this paper, I argue that methodological nationalism is not only empirically inaccurate, but also normatively problematic, because its assumptions prevent migration ethicists from properly theorising about discrimination. I begin by briefly presenting methodological nationalism and clarifying some misconceptions. I also identify some features that would make a policy discriminatory and show that many contemporary migration policies are discriminatory. Looking at three variants of methodological nationalism (naturalisation, territorialisation, and ignorance), I argue that methodological nationalism marginalises concerns about discrimination in migration ethics and prevents migration ethicists from developing accounts that would be able to counter xenophobic arguments. Last, I consider the implications of my argument for migration ethics.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".