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Record W2716557023 · doi:10.1080/21650020.2014.893199

The impact of heritage investment on public attitudes to place: evidence from the Townscape Heritage Initiative (THI)

2014· article· en· W2716557023 on OpenAlexaff
Alan Reeve, Robert Shipley

Bibliographic record

VenueUrban Planning and Transport Research · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsRealmInvestment (military)Public investmentPerceptionQuality (philosophy)LotteryPolitical sciencePublic administrationPoliticsEconomicsPsychologyLawPublic fund

Abstract

fetched live from OpenAlex

This paper is concerned with public perceptions and attitudes to heritage townscapes, and how these might be influenced by investment in such places, focused on their public realm, and building restoration and improvement as a catalyst for urban regeneration. It draws on a ten-year study of the impact of the Townscape Heritage Initiative, funded by the Heritage Lottery Fund, on a sample of 16 cases across the UK. By comparing an analysis of changes in townscape quality over this period, with changes in public perceptions (captured through the use of a household survey in all 16 cases at three points in the ten-year period), it draws empirically grounded conclusions about the influence of heritage investment on attitudes and perceptions to the quality of the local environment. The findings from the research suggests that public attitudes are positively influenced by programmes of investment in the built heritage, but that this influence is complex and is not as robust as the physical regeneration itself. The paper also reflects on the relative influence of the post-2008 economic recession on public attitudes to place compared with the influence of heritage investment.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.102
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.183
GPT teacher head0.432
Teacher spread0.249 · 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 teacher head, not a consensus.

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

Citations11
Published2014
Admission routes1
Has abstractyes

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