Globalization and language in contact : scale, migration, and communicative practices
Bibliographic record
Abstract
Space, scale and accents: constructing migrant identity in Beijing / J.K. Dong & J. Blommaert -- Goffman and globalisation: frame, footing and scale in migration-connected multilingualism / J. Collins & S. Slembrouck -- The spaces of language: the everyday practices of Somali refugee and asylum seeker young people / G. Valentine, D. Sporton & K. Bang Nielsen -- Immigration in Catalonia: marking territory through language / J. Pujolar -- Either and both the changing concept of living space among Polish post-communist migrants to the United Kingdom / A. Galasinska & O. Kozlowska -- Canada meets France: recasting identities of Canadianess and Francit through global economic exchanges / G. Budach -- Changing participation in changing practice: uses of language and literacy among Portuguese migrant women in the UK. / C. Keating -- A relational understanding of language practice: interacting time-spaces in a single ethnographic site / C. B. Vigouroux -- Transnational flows, networks and transcultural capital: reflections on researching migrant networks through linguistic ethnography / U. H. Meinhof -- Just one day like today: the notion of scale and the analysis of space time orientation in narratives of displacement / M. Baynham -- Weighing the scales: recontextualisation as horizontal scaling / C. Kell -- From space to spatialization in narrative studies / A. De Fina.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.007 | 0.030 |
| Scholarly communication | 0.014 | 0.009 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".