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Record W2476480529 · doi:10.1017/chol9780521431415.006

England: South-West

2000· book-chapter· de· W2476480529 on OpenAlexaboutno aff
Jonathan Barry

Bibliographic record

VenueCambridge University Press eBooks · 2000
Typebook-chapter
Languagede
FieldEconomics, Econometrics and Finance
TopicHistorical Economic and Social Studies
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)GeographyPopulationTourismUrbanizationPeriod (music)AsideArchaeologySocioeconomicsDemographyEconomic growthSociologyArt

Abstract

fetched live from OpenAlex

the six counties in the South-West of England (Gloucestershire, Wiltshire, Dorset, Somerset, Devon and Cornwall) are not now associated strongly with urbanisation. Apart from Bristol and Plymouth, the region is predominantly one of small and medium-sized towns. The origins of this modern pattern, in contrast with the more heavily urbanised Midlands and (parts of) the North, lie in the period covered here. Yet it would be misleading to portray this period as one of urban decline in the South-West. Not only was there a more than threefold increase in the urban population of the region between 1660 ( c. 225,000) and 1841 (just under 880,000), but even in 1841 the South-West, with 40 per cent of its population in towns, was as urbanised as England generally, leaving London aside (see Table 2.6).1 If urban growth in the previous centuries was less spectacular than elsewhere, this was in part because of the strong urban infrastructure already in place, with over a quarter of the region’s people living in towns by 1660, rising to almost 37 per cent by 1801. Furthermore, if the region lacked an outstanding major new town based on manufacturing and commercial success, it had many smaller ones, notably in Cornwall and in the clothing districts around Bristol, and it had the two greatest inland spas – Bath (see Plates 3 and 28) and Cheltenham, the latter the fastest growing large English town between 1801 and 1841. The leisure and tourism industry they personified was already transforming the coastal towns from Weymouth along the south Devon coast and round to Weston-super-Mare and Clevedon on the Bristol Channel.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.290
Threshold uncertainty score0.969

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0030.001
Scholarly communication0.0060.004
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.2900.074

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 head0.031
GPT teacher head0.170
Teacher spread0.139 · 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 designTheoretical or conceptual
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
Published2000
Admission routes1
Has abstractyes

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