Ethnicity in a globalizing world: borders, boundaries, and virtual communities
Bibliographic record
Abstract
Num mundo globalizado, os tradicionais limites e fronteiras étnicos e nacionais estão a perder a sua relevância para o estudo da diversidade cultural. Um número crescente de antropólogos e de sociólogos apontam para a separação entre o território e cultura. Outros perguntam-se se a compressão do tempo e do espaço, que acompanhou a globalização, criou, mesmo nas regiões mais remotas, uma consciência e algum grau de experiência mediada do mundo global. Isto pode estar a resultar não só na formação de um novo nível de cultura mundial, mas também na diminuição de repertórios culturais. Enquanto a importância do espaço e das fronteiras físicas diminui na comunicação quotidiana, também se está a tornar possível construir e manter laços étnicos sob novas formas. Por exemplo, as fronteiras entre a nação de origem e o país de emigração tornou-se difusa no caso das diásporas étnicas. Isto levanta a questão de saber em que medida as comunidades virtuais podem constituir uma alternativa a unidades sociais limitadas, tais como as comunidades étnicas. Este artigo debate estas questões no estudo antropológico e sociológico da etnicidade In a globalizing world, traditional ethnic and national boundaries and borders are becoming less relevant to the study of cultural variation. A growing number of anthropologists and sociologists point to the delinking of territory and culture. Others raise the issue of whether the compression of time and space that has accompanied globalization has fostered, even in the remotest areas, an awareness and some degree of mediated experience of the world at large. This might be resulting not only in the formation of a layer of world culture but also in the shrinking of cultural repertoires. As the importance of physical space and boundaries declines in everyday communication, it is also becoming possible to construct and maintain ethnic ties in new ways. For example, the boundaries between the mother nation and the country of immigration have become blurred in the case of ethnic diasporas. This raises the issue of to what extent virtual communities might constitute an alternative to bounded social units such as ethnic communities. This article discusses these issues in the anthropological and sociological study of ethnicity.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.016 |
| Scholarly communication | 0.013 | 0.012 |
| Open science | 0.001 | 0.007 |
| 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".