Why Theatre? Examining Transferable Skills from Theatre Degrees to Non-Creative Professions
Bibliographic record
Abstract
There is stigma surrounding those who choose to obtain drama degrees at the undergraduate level, especially if they have no interest in pursuing a theatre-related career. The goal of this study was to determine if there are skills obtained from theatre training at the undergraduate level that are advantageous in non-creative professions. I sent out a survey to drama alumni in non-theatre-related professions to determine if they believed they gained transferable skills from their theatre degree at Queen’s University that have been helpful in their current careers. I then interviewed five drama alumni to get a more in-depth understanding of how drama has been helpful in their professions. Their careers were in the areas of law, sales management, public relations, global development, and politics, giving a diverse range of perspectives on the usefulness of their drama degrees. Finally, I analyzed both the survey responses and interviews and discovered that there were several skills the drama alumni attributed to their theatre training at Queen’s University. My study provided evidence that graduates of our drama program brought skills in public presentation, teamwork, empathy, organization, and adaptability to their careers outside the arts.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".