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Record W4377241054 · doi:10.1017/s0960777322000996

Patterns of Irish Civil War Memory in Later-Generation Oral Histories

2023· article· en· W4377241054 on OpenAlexaff
Gavin M. Foster

Bibliographic record

VenueContemporary European History · 2023
Typearticle
Languageen
FieldPsychology
TopicMemory, Trauma, and Commemoration
Canadian institutionsConcordia University
Fundersnot available
KeywordsSpanish Civil WarIrishPoliticsSilenceOral historyNationalismCollective memoryPolitics of memoryHistoryTraumatic memoriesPeriod (music)Political economySociologyPolitical scienceLawPsychologyAestheticsArchaeologyArt

Abstract

fetched live from OpenAlex

No phase of Ireland's 1913–23 revolution has proven as challenging for social remembrance as the 1922–3 civil war. While the conflict structured party politics and fuelled political agendas for decades, its toxic memory was widely regarded as best forgotten. Yet, as Beiner has argued, even ‘when communities try . . . to forget discomfiting historical episodes’, they still ‘retain muted recollections’. Drawing on oral history interviews, this article examines civil war silences and selective memories transmitted across generations among families and communities impacted by the conflict. Themes to be touched on include silence; memories of incidents of violence and other traumatic experiences; partisan animosities and political reverberations of the period; and the material and physical manifestations of civil war memory. Consideration of these patterns illuminates complexities in nationalist memory in Ireland, while it suggests broader insights into how societies and communities make sense of divisive historical episodes.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.004
Science and technology studies0.0040.007
Scholarly communication0.0060.002
Open science0.0010.006
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.111
GPT teacher head0.286
Teacher spread0.175 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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
Published2023
Admission routes1
Has abstractyes

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