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Record W2945406563 · doi:10.1093/cje/bez031

Occupational structure in Ireland in the nineteenth century: data sources and avenues of exploration

2019· article· en· W2945406563 on OpenAlexaboutno aff
Jason Begley, Frank Geary, Tom Stark

Bibliographic record

VenueCambridge Journal of Economics · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHistorical Economic and Social Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIrishCensusFaminePopulationDemographic economicsPrimary sector of the economyEconomicsEconomyTertiary sector of the economyQuarter (Canadian coin)Period (music)GeographyDemographySociology

Abstract

fetched live from OpenAlex

Abstract This paper considers structural change in post-Famine Ireland through an examination of changes in the allocation of the labour force across three broad production sectors: primary, secondary and tertiary. To do so, it makes extensive use of the Irish Census of Population from 1821 to 1911 as a source of occupational information. While there are a number of concerns with these returns, outlined and explored here, the Irish census remains the most complete source of information available on male and female labour force activity and occupations in Ireland during this period. The outcome of this exercise is a picture of Irish primary, secondary and tertiary sector employment during the latter half of the nineteenth century that is consistent with that of an economy undergoing a development transition: modernising albeit slowly. While Ireland was the poorest region of the UK economy, it was one of the richer European economies in terms of GDP per head and undergoing a development transition similar to a number of European economies during this period.

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)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.194
Threshold uncertainty score0.385

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0100.016
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.055
GPT teacher head0.234
Teacher spread0.178 · 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 designObservational
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

Citations1
Published2019
Admission routes1
Has abstractyes

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