White enough, not white enough: racism and racialisation among Poles in the UK
Bibliographic record
Abstract
This paper discusses race, racialisation and whiteness in relation to Eastern European migrants living in Western Europe. Focusing on Poles in the UK, it examines both Polish migrants’ experiences of racism as well as their own investment into racial exclusions of other racialised groups. The paper interrogates how migrants navigate their peripheral whiteness in broader racial hierarchies of Eastern European in-betweenness that are both historically rooted and constantly negotiated. Benefitting from relatively easy access to the UK, Polish migrants occupy at once a racially privileged and racially marginal position that echoes historical tensions around the place of Eastern Europe in wider racial hierarchies of Europeanness. While being white enough to engage in racial exclusions Eastern Europeans are at the same time not white enough to escape racialisation. Drawing on semi-structured interviews with Poles in the UK conducted between 2019–2020 the paper offers insight into complex racialising practices of Polish migrants when they are both racialised and able to benefit from their position as ‘paler migrants’ to distance themselves from other migrants as well as ‘darker citizens’. It contributes to scholarship on racialisation of East–West movers within Europe, in-betweenness and whiteness.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".