Bibliographic record
Abstract
This introduction to the second volume of The Routledge Companion to Twentieth Century British Theatre and Performance is written when everyone involved in the project has lived through a quarter of the twenty-first century. At the turn of the century in 2000, very few of us could have predicted the extremity of what lay ahead in terms of continuous geopolitical crisis: contested ideologies and belief systems, unequal resources hoarded by the global north and the wars and human devastation which have resulted. The year 2007 brought another major international economic meltdown precipitated by the growth of unimaginably wealthy corporations whose activities have long since ceased to be controlled within the bounds or the local interests of nation states. Perhaps most alarmingly, predictions and actual evidence of climate catastrophe are on the increase. More specifically, in relation to this volume, individual research and writing and associated editorial challenges have been conducted within the context and lingering after-effects of the Covid-19 pandemic. It remains to be seen whether this global ‘event’ will be deployed by future historians as a significant temporal marker: if pre- and post-Covid will take on the same epoch-defining qualities long associated with the two ‘World Wars’ of the twentieth century. What is certainly clear are its immediate and ongoing effects on our writing and research cultures, and on many lives.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.464 | 0.237 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".