MétaCan
Menu
Back to cohort
Record W2999070276 · doi:10.1007/s41636-019-00219-2

“Against Shameless and Systematic Calumny”: Strategies of Domination and Resistance and Their Impact on the Bodies of the Poor in Nineteenth-Century Ireland

2020· article· en· W2999070276 on OpenAlexfundno aff
Jonny Geber, Barra O’Donnabhain

Bibliographic record

VenueHistorical Archaeology · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHistorical Economic and Social Studies
Canadian institutionsnot available
FundersJohan och Jakob Söderbergs stiftelseQueen's UniversityIrish Research CouncilUniversity College CorkQueen's University BelfastWellcome TrustWellcome
KeywordsResistance (ecology)HistoryBiologyEcology

Abstract

fetched live from OpenAlex

Mid-Victorian British characterizations of Ireland and much of its population blamed race and "moral character" for the widespread poverty on the island. The Irish poor were portrayed as a "race apart" whose inherent failings were at least partly to blame for the mortality they suffered during the Great Famine of 1845-1852. Recent excavations at Kilkenny workhouse and Spike Island convict prison have produced skeletal assemblages from this critical period. These collections have enabled bioarchaeological analysis of parameters mentioned by the Victorians as indicative of the distinctiveness of the Irish poor: stature, interpersonal violence, and tobacco use. Bioarchaeological data indicate that the differences between Irish and British populations in stature and risk of violence were exaggerated. Such characterizations, we argue, were part of a strategy of "Othering" that served to legitimize colonial domination. This exertion of power did not go uncontested, as the pattern of tobacco use may be indicative of forms of passive resistance.

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)0.003
metaresearch head score (Gemma)0.005
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 score0.191
Threshold uncertainty score0.379

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0120.044
Scholarly communication0.0060.003
Open science0.0010.007
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.022
GPT teacher head0.203
Teacher spread0.181 · 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

Citations10
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueHistorical ArchaeologySame topicHistorical Economic and Social StudiesFrench-language works237,207