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Record W3159139303 · doi:10.21226/ewjus642

Internal Colonialism, Alien Rule, and Famine in Ireland and Ukraine

2021· article· en· W3159139303 on OpenAlexvenueno aff
Michael Hechter

Bibliographic record

VenueEast/West Journal of Ukrainian Studies · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicIrish and British Studies
Canadian institutionsnot available
Fundersnot available
KeywordsFamineIrishUkrainianPoliticsAlienColonialismResentmentPolitical sciencePolitical economyHistoryEconomic historyDevelopment economicsGeographySociologyLawCitizenshipEconomics

Abstract

fetched live from OpenAlex

The Irish famine of the mid nineteenth century and the Ukrainian famine of the twentieth century have been the subject of large and quite contentious literatures. Whereas many popular explanations of the Irish famine attribute it to the English government’s infatuation with laissez-faire economic doctrines, by contrast the Ukrainian famine has often been ascribed to Stalin’s resentment of Ukraine’s resistance to the Soviet revolution. This essay suggests that despite their many differences, during these years both Ireland and Ukraine can be considered to have been internal colonies of their respective empires. The key implication of this conception is that these appalling famines arose from a common underlying cause: namely, the inferior political status of these regions relative to that of the core regions of these states. One of the defining characteristics of internal colonies is that they often suffer from alien rule. Alien rulers are typically indifferent to the welfare of the residents of the culturally distinctive regions within their borders. Due to this indifference, both the British and Soviet central rulers cast a blind eye to the fate of the Irish and Ukrainian peasants.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.113
Threshold uncertainty score0.224

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.011
Scholarly communication0.0040.001
Open science0.0000.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.030
GPT teacher head0.331
Teacher spread0.300 · 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 designNot applicable
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

Citations6
Published2021
Admission routes1
Has abstractyes

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