‘Journey to the future’: imaginaries and motivations for homeland trips among diasporic Armenians
Bibliographic record
Abstract
Abstract This article highlights diasporic migrants' transnational linkages with and trips to their homeland. Second and later generations of diasporic Armenians, predominantly from the USA and Canada, claim to travel to the ancestral homeland in Armenia not as heritage tourists to see the holy Mount Ararat but to invest in local development through social work. Based on ethnographic research, in‐depth interviews with volunteers and text materials, this article identifies those specific features of the contemporary diasporic ‘sacred journey’ that differ from conventional return migrations. This new inter‐continental migratory path between North America and Armenia has a temporary character. By analysing the range of reasons why young professional Armenian‐Americans and Armenian‐Canadians should choose to travel the long distance to offer their services, this article provides insight into the decision to become a volunteer in Armenia and the ways non‐profit diasporic organizations channel and mobilize this transnational activity. The study shows that ‘ethnic’ volunteers are highly conscious of the modern understanding of mobility as being a marker of personal social status within the society in which they grew up. The study of a variety of imaginaries among members of a paradigmatic diasporic group, such as Armenians, shows how second and later diasporic generations take advantage of their multi‐cultural background to become transnational global actors.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| 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".