A Woman's Words: Emer and Female Speech in the Ulster Cycle
Bibliographic record
Abstract
A Woman's Words is the first in-depth analysis of Middle Irish literature from a feminist standpoint, and the first formal critical discussion of the representation of female speech in medieval Irish literature. Joanne Findon analyses the representation of Emer, the wife of the great Irish hero Cu Chulainn, in four linked medieval Irish tales, and discusses Emer's ability to use powerful, effective words to change her fictional world and the audience's reading of that fictional world. A Woman's Words considers Emer as a literary figure rather than a mythic archetype or a reflection of a pre-Christian Celtic goddess. Emer and the narratives she inhabits are discussed as literary constructs, and are considered within the historical and legal milieu in which these tales were told, recorded, and read. Findon places Emer within the wider context of medieval literature in general as an unusual and compelling example of a heroic secular woman, married and fully integrated into her aristocratic society and yet capable of speaking out against its abuses. Her freedom to speak and be heard is remarkable in the light of prevalent later medieval impulses to silence women. By employing speech act theory to analyse Emer's discourse, and by viewing and interpreting the texts through the lens of current feminist criticism, Joanne Findon seeks to bring Middle Irish literature into the arena of current debates, particularly among feminist medievalists, and to offer a new approach to reading female characters in medieval Irish literature.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.013 | 0.018 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".