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Record W1099441940 · doi:10.3138/cjh.ach.50.2.262

William Beveridge in New Zealand: Social Security and World Security

2015· article· en· W1099441940 on OpenAlexvenueno aff
John Stewart

Bibliographic record

VenueJournal of History · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical and Economic history of UK and US
Canadian institutionsnot available
Fundersnot available
KeywordsSocial securityWelfare stateGovernment (linguistics)SociologyPolitical economyState (computer science)Political scienceWelfarePublic administrationLawPolitics

Abstract

fetched live from OpenAlex

In 1948 William Beveridge, one of the architects of Britain’s welfare state, visited New Zealand and gave public addresses focused in particular on two themes: social security and world security. In the former, Beveridge outlined his welfare philosophy which he used to critique the New Zealand Labour government’s policies. In the latter, Beveridge proposed the re-ordering of world affairs to ensure no further wars and to resist Soviet totalitarianism. For Beveridge, social security and world security were indissolubly linked: it was pointless having the former unless the latter could be guaranteed, and moreover, it was liberal societies of the type he proposed that were best equipped to promote harmonious international relations. In all of his speeches, Beveridge emphasized New Zealand’s essentially British nature. Both countries were members of the same “family” and so had common cause as well as a shared history in social and world affairs.

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)0.002
metaresearch head score (Gemma)0.004
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.356
Threshold uncertainty score0.709

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0060.010
Scholarly communication0.0060.010
Open science0.0010.003
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0080.001

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 head0.041
GPT teacher head0.277
Teacher spread0.236 · 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

Citations4
Published2015
Admission routes1
Has abstractyes

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