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Record W4205258593 · doi:10.3390/genealogy6010003

Elegies and Laments in the Nova Scotia Gaelic Song Tradition: Conservatism and Innovation

2021· article· en· W4205258593 on OpenAlexaboutno aff
Robert Dunbar

Bibliographic record

VenueGenealogy · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicScottish History and National Identity
Canadian institutionsnot available
Fundersnot available
KeywordsAristocracy (class)HistoryContext (archaeology)PraiseLiteratureClanPoetryGenealogySociologyArtLawPoliticsArchaeologyPolitical scienceAnthropology

Abstract

fetched live from OpenAlex

Gaelic-speaking emigrants brought with them a massive body of oral tradition, including a rich and varied corpus of song–poetry, and many of the emigrants were themselves highly skilled song-makers. Elegies were a particularly prominent genre that formed a crucially important aspect of the sizeable amount of panegyric verse for members of the Gaelic aristocracy, which is a tradition dating back to the Middle Ages. This contribution will demonstrate that elegies retained a prominent place in the Gaelic tradition in the new world Gaelic communities established in many parts of Canada and in particular in eastern Nova Scotia. In many respects, the tradition is a conservative one: there are strong elements of continuity. One important difference is the subjects for whom elegies were composed: in the new world context, praise for clan chiefs and other members of the traditional Gaelic aristocracy were no longer of relevance, although a small number were composed primarily out of a sense of personal obligation for patronage shown in the Old Country. Instead—and as was increasingly happening in the nineteenth century in Scotland, as well—the deaths of new community leaders, including clergy, and other prominent Gaels were recorded in verse. The large number of songs composed to mark the deaths of community members is also important—particularly young people lost at sea and in other tragic circumstances, occasionally in military service, and so forth. In these song–poems, we see local poets playing a role assumed by song-makers throughout Gaelic-speaking Scotland and Ireland: that of spokespeople for the community as a whole.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.906
Threshold uncertainty score0.640

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.081
GPT teacher head0.261
Teacher spread0.180 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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