Bibliographic record
Abstract
Drawing on John MacInnes’s writings on the òrain-luaidh and what he calls the ‘panegyric code’ in Gaelic poetry, this essay argues that the òrain-luaidh of Scotland and a number of genres of women’s oral poetry in Irish derive from a single oral-formulaic tradition that seems to have belonged particularly to women, and to have been dominated by women’s concerns until responsibility for the waulking of cloth passed to men in the migrant Gaelic-speaking communities of eastern Canada. The Irish texts quoted are best exemplified by the caoineadh, or lament for the dead, but also include joke laments, lullabies, work songs, and religious poetry. They share numerous themes and formulas, along with important features of diction, metre and composition, not only with waulking songs recorded in twentieth-century Scotland, but also with the luinneagan composed by Màiri nighean Alasdair Ruaidh (Mary MacLeod) in the seventeenth century.
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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 | 0.001 | 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 | 0.007 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.032 | 0.007 |
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".