MétaCan
Menu
Back to cohort
Record W2160626558 · doi:10.1353/jsh.0.0186

Country Living, Country Dying: Rural Suicides in New Zealand, 1900-1950

2009· article· en· W2160626558 on OpenAlexaff
John C. Weaver, Doug Munro

Bibliographic record

VenueJournal of Social History · 2009
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicNew Zealand Economic and Social Studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPovertyDebtBoomCommodityDominance (genetics)Political scienceEconomic growthDevelopment economicsBusinessEconomicsMarket economyFinance

Abstract

fetched live from OpenAlex

The quality of rural living has long attracted contradictory assessments. In New Zealand where farm produce figured pre-eminently in the economy, opposing assessments abounded. Politicians tended to gloss over rural hardships, favoured an Arcadian myth, and initiated schemes to alleviate poverty by putting people on the land; dissenting portrayals emerged from the country's realist literature. Historians have taken sides but, in common with social historians everywhere, their assessments of the quality of life turn on fragmentary evidence. Moreover, the typicality of well-documented cases is open to question. First hand accounts by farmers, farm labourers, and farm women are scarce. A study of inquests into the suicides of over a thousand rural New Zealanders overcomes a dearth of information and provides nation-wide coverage over many decades. Witnesses' depositions afford glimpses into the material and emotional crises during booms, slumps, depressions, and wars. Rural men had a much higher suicide rate than urban men. Farm operators endured debt and commodity price fluctuations, while farm labourers-essential to farm profitability-faced emotional, financial, and physical hazards from youth to old age. Rural life for many offered no unqualified release from the stresses of the modern age.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.569
Threshold uncertainty score0.866

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.002
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.023
GPT teacher head0.217
Teacher spread0.194 · 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

Citations4
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Social HistorySame topicNew Zealand Economic and Social StudiesFrench-language works237,207