Bibliographic record
Abstract
Ideas of belonging, cultural identity, and social relations based on ancestral connection, blood, and primordial kinship, have a contradictory presence in cultural theory and public culture. The search for alternatives to fixed, essentialist, and exclusive ways of imagining culture and belonging has been central to recent cultural theory and cultural geography. This has involved much attention to cultural routes, mobility, and hybridity and a critique of cultural roots, fixity, and purity in response to increasing transnational flows, the experience of displaced people, racism, and ethnic fundamentalism. Yet discourses of indigeneity and new migration patterns, as well as cultural globalisation more widely, have also prompted the growth in genealogy amongst ‘settler’ groups in Australia, Canada, New Zealand, and the United States who search for European, and often specifically Irish, roots. In this paper I explore the relationships between ideas of nation, ancestry, and diaspora. I focus on what happens when questions of nationality, ethnicity, and identity meet in the practice of ancestral research in Ireland, and begin to track the spatially differentiated cultural politics of genealogy. As the language of genealogy travels with Irish roots tourists and through electronic networks, the implications of genealogical practices and identifications can mutate so that what may be a politically regressive turn to ethnic purity and racial discourse in one context can, in another, productively unsettle older exclusive versions of belonging. For both individual and collective identities, genealogical projects can have unsettling results.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.010 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.035 | 0.008 |
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".