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Record W7055746862

Do Edinburgh students go to the theatre and participate in audiences? A qualiquantitative analysis.

2020· dissertation· en· W7055746862 on OpenAlexaboutno aff

Bibliographic record

VenueQueen Margaret University Publications Repository (Queen Margaret University) · 2020
Typedissertation
Languageen
FieldEngineering
TopicLaser Design and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsOrder (exchange)PopulationMovie theaterQuarter (Canadian coin)Cultural institutionHigher education
DOInot available

Abstract

fetched live from OpenAlex

Theatre in Edinburgh is a very important part of the cultural landscape of the city. As one of the cultural hubs in the world – hosting the world-famous Edinburgh Fringe Festival every August – Edinburgh has a large history with the theatrical arts. The city is also home to a large number of theatres that cover a spectrum of differences, including large receiving houses; producing houses; and smaller regional theatres, to name a few. However, theatre is also seen as a pass time for older members of society. Edinburgh also has a rich history in academia, producing breakthrough discoveries and playing host to 4 Higher Education institutions in addition to other Further Education institutions. This study looks to explore and answer the question “Do Edinburgh’s Student Population Go to View Theatre in Traditional Theatre Buildings?”. This question will be answered qualitative, quantitative and quali-quantitative methods in order to gain the most rounded collection of data to gain the most in-depth answer for the extent Edinburgh’s students participate in theatre audiences. The methods used are an online survey; a group discussion; and an interview with a former Box Office supervisor at the Lyceum. The study found that the group sampled did go to the theatre and engaged because they wanted to go and see live performances – typically avoiding live streamed performances or recorded performances for cinema viewing. The study also found that there were barriers for students who wanted to engage with theatrical productions, particularly to do with pricing and student related deals – with students citing that they would need to gamble and try to get a last minute ticket on the day. The data also shows that any potential ticket deals lack the advertisement to gain the maximum use from the student population.

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 categoriesMeta-epidemiology (narrow)
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 score0.419
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.006
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0020.000
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 head0.014
GPT teacher head0.240
Teacher spread0.226 · 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 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
Published2020
Admission routes1
Has abstractyes

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