Making Sense of Shakespeare: a Cultural Icon for Contemporary Audiences
Bibliographic record
Abstract
The works of William Shakespeare are more popular in the 21st century than ever before, Why are theatre and audiences around the globe still drawn to his work? How do they make sense of these texts in ways that resonate with their cosmopolitan, contemporary audiences? This article uses the findings of a study interviewing 35 theatre professionals in Canada, Finland and the United Kingdom to explore these issues. Theoretically and methodologically, it is a bricollage, drawing on a range of approaches including Foucault’s discourse analysis, Hobsbawm’s invented traditions and Dervin’s Sense-Making to understand participants sense-making as an affective, embodied social practice. It argues that attempting to understand the significance of a major cultural icon such as Shakespeare in contemporary cosmopolitan civil society needs to recognise the many meanings, roles and significances that surround him and that this complexity makes it unlikely that any one theoretical lens will prove adequate on its own. DOI: http://dx.doi.org/10.5130/ccs.v5i3.3640
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 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 | 0.011 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.023 | 0.059 |
| Scholarly communication | 0.018 | 0.011 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".