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Regenerating Cultural Identity through Industrial Heritage Tourism: Visitor Attitudes, Entertainment and the Search for Authenticity at Mills, Mines and Museums of Maritime Canada

2015· article· en· W2533873971 on OpenAlexaffabout
Robert Summerby‐Murray

Bibliographic record

VenueLondon Journal of Canadian Studies · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Management and Preservation
Canadian institutionsSaint Mary's University
Fundersnot available
KeywordsIndustrial heritageVisitor patternTourismCultural heritageCultural heritage managementPoliticsIdentity (music)Cultural identityEntertainmentCultural landscapeSpectacleConstruct (python library)SociologyHistoryEnvironmental ethicsMedia studiesAestheticsArchaeologyPolitical scienceSocial scienceArtLaw

Abstract

fetched live from OpenAlex

This essay analyses visitor attitudes to industrial heritage at a variety of former industrial sites, ranging from former coal mines, shipbuilding yards and steampowered mills to a reconstructed waterfront. In addition, a comprehensive industrial museum provided a venue for further critique of the means by which the industrial past contributes to a regeneration of cultural identity in Maritime Canada. The range of former industrial sites reflects the multiple narratives of deindustrialisation affecting the Canadian provinces of Nova Scotia, New Brunswick and Prince Edward Island for much of the twentieth century while visitor responses to a detailed survey indicate that a focus on industrial heritage is a highly-valued component of respondents’ understanding of the region’s cultural identity. The essay notes, however, that this representation of cultural identity is highly problematic and replete with contradictions, most notably between respondents’ desires for authenticity and the necessarily sanitised landscapes required for cultural tourism. Similarly, designers and managers of industrial heritage may be motivated to construct heritage landscapes which prioritise entertainment and spectacle and down play significant environmental, social and political elements of the former industry. From these examples in Maritime Canada, it is clear that visitors encounter significant complexity in their experience of the industrial past. This complexity provides both opportunity and challenge in the use of the industrial past as a means of cultural regeneration in the region.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.248
Threshold uncertainty score0.317

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.182
GPT teacher head0.288
Teacher spread0.107 · 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.

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

Citations3
Published2015
Admission routes2
Has abstractyes

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