Co-Ethnic in Private, Multicultural in Public: Group-Making Practices and Normative Multiculturalism in a Community Sports Club
Bibliographic record
Abstract
This paper explores how multiculturalism is enacted and negotiated among Brazilian and Portuguese migrants at a football (soccer) club in Amsterdam, the Netherlands. The authors use the lens of everyday multiculturalism to analyse the tension between public expectations about intercultural ‘mixing’ and actual intercultural engagement in practice. Drawing on ethnographic fieldwork, we discuss how club members negotiate the national discourse that recognises cultural differences yet prescribes intercultural mixing in the public sphere. The findings show that meeting co-ethnics is one of the club members’ primary motivations for participating in the football club, whereas interacting with people with culturally diverse backgrounds is not a leitmotif. Everyday group-making practices among Portuguese and Brazilian players reinforce group boundaries and constrain intercultural interaction, thereby challenging normative multiculturalism that prescribes ethnic mixing. The paper concludes that members’ multicultural presentation of their club provides a socially accepted environment for ethnically concentrated sport participation.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.020 | 0.021 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".