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Borrowed robes: the educational value of costumed interpretation at historic sites

2004· article· en· W7135383055 on OpenAlexaboutno aff

Bibliographic record

VenueResearch at the University of Copenhagen (University of Copenhagen) · 2004
Typearticle
Languageen
FieldArts and Humanities
TopicCrafts, Textile, and Design
Canadian institutionsnot available
Fundersnot available
KeywordsInterpretation (philosophy)Value (mathematics)Field (mathematics)Exposition (narrative)Period (music)

Abstract

fetched live from OpenAlex

Pressure to develop vulnerable historic sites into competitive commercial operations has led to controversial interpretive techniques being introduced by aggressive marketing managers.Scarce resources have been invested in largely unproven technological and other innovative methods of presentation.This paper looks at the employment of costumed interpreters at historic sites, what they claim to offer visitors, and whether their services match visitors' needs.It reports the findings of an investigation into what visitors want from historic sites and the extent to which costumed interpreters contribute to their experiences.The study reported here compared the performance of 12 historic sites in four countries: two European (Sweden and the UK) and two North American (Canada and the USA); with the participation of 589 visitors.The study provides clear recommendations for site managers as to the value of costumed interpretation and offers guidelines on the levels of investment (in reproduction costume and staff training) that guarantee visitors an educational experience during their visits to historic sites.

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)0.003
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0030.004
Scholarly communication0.0040.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.001

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 head0.049
GPT teacher head0.257
Teacher spread0.208 · 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 designQualitative
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
Published2004
Admission routes1
Has abstractyes

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