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Record W3148867872 · doi:10.32469/10355/78156

The employment value of an undergraduate degree in theatre arts in the U.S.

2020· dissertation· en· W3148867872 on OpenAlexaff
Melanie Dreyer-Lude

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsEmployabilityThe artsValue (mathematics)PerceptionPerforming artsVariety (cybernetics)Work (physics)PsychologyPolitical scienceSociologyVisual artsPedagogyArtEngineeringMathematicsStatistics

Abstract

fetched live from OpenAlex

During lean times, administrators must make hard decisions about which programs stay and which must go. Arts departments are particularly vulnerable when traditionally derived enrollment and employability factors are used to determine where to implement cuts. While only a minority of Theatre Arts graduates will find work as artists, most do find employment in a variety of fields. Because current labor statistics fail to capture the complexity of the employment patterns of these graduates, Theatre Arts departments are vulnerable to downsizing. This study investigated the employment patterns of theatre graduates in the United States, the skills applied to current employment, and their perceptions of the value of their theatre arts degree. Findings from a survey of 487 participants provided a new map of the employment patterns of Theatre Arts graduates, identifying how and where graduates found employment and whether the skills acquired with a Theatre Arts degree contributed to a perception of value for dollars spent.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.075
GPT teacher head0.333
Teacher spread0.258 · 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 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

Citations0
Published2020
Admission routes1
Has abstractyes

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