Mapping the national web: Spaces, cultures and borders of diasporic mobilization in the digital age
Bibliographic record
Abstract
Abstract National web is a series of interlinked online spaces, generated and visited by users who share a common national identity, language and/or an interest in a particular country. For diasporic communities living outside of their country of origin, national web is an entity that emerges through the production and circulation of culturally significant content and genres. A wealth of textual and visual data, produced in the process of mediated communication among diasporic actors, turn social media into a point of entry for mapping national webs. In this paper, we explore hyperlinking behaviours among Ukrainian Canadians to map geographic, linguistic and geopolitical boundaries of the Ukrainian national web. Shining light on the spaces and cultures of diasporic mobilization in the digital age, we identify distinct web spheres that mediate the Ukrainian Canadians’ relationship to their country of origin, demonstrating their elevated significance in the current geopolitical context.
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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 | 0.004 | 0.005 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.000 | 0.000 |
| 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".