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Record W2522820137

Sir John Eldon Gorst and British Social Policy 1875-1914

2016· dissertation· en· W2522820137 on OpenAlexfundno aff
Olwen Claire Niessen

Bibliographic record

VenueUWSpace (University of Waterloo) · 2016
Typedissertation
Languageen
FieldSocial Sciences
TopicPolitical and Economic history of UK and US
Canadian institutionsnot available
FundersGovernment of Ontario
KeywordsPolitical scienceSociologyEconomic historyLawTheologyHistoryPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

The period of Liberal rule in Britain between 1906 and 1914 is justly remembered for its social reforms. The "New Liberalism" of these years produced the social legislation which constituted the nucleus of what \nis now the British "Welfare State". These measures represented a reversal of the individualistic, laissez-faire doctrines of the nineteenth century, a reversal effected partly through the efforts of social investigators, partly as a result of hard-headed political expediency and the ambitions of particular Government ministers, and partly the Liberal Government's response to the threat of Socialism. These reforms also resulted from the efforts of various individuals and many of them, particularly those of \nCabinet rank, such as Lloyd George and Winston Churchill, have received recognition from historians for their efforts. Other equally concerned and energetic reformers have virtually been ignored. One of these is Sir John Eldon Gorst. Through examination of Gorst's speeches in the House of Commons, his writings in the periodic press, and his communications to the Times, plus reports therein of his various activities connected with social reform measures, it is shown that Gorst made a significant contribution to late Victorian and Edwardian social legislation.

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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.413
Threshold uncertainty score0.822

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0060.007
Scholarly communication0.0030.001
Open science0.0000.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0150.002

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 head0.011
GPT teacher head0.223
Teacher spread0.212 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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