Culture and Power: The Plots of History in Performance
Bibliographic record
Abstract
Culture and Power: The Plots of History in Performance is a collection of essays on the configuration of history as text, including the visual, with a particular focus on the performance of historical plots. Contributors include distinguished scholars from parts of the world as far apart as Toronto and Istanbul, Singapore and Cardiff, or Berlin and Alicante, in all walks of academic life, from emeritus professors to recent PhDs. Covering a broad spectrum between cultural studies and metahistory, from politics to literature, and exploring the various performative aspects of history writing, in their full range, from myth to the sublime, the whole endeavours to be greater than the sum of its parts. The essays begin by questioning traditional historiography and the problems of referentiality it entails. Locating history-making in the primal scene of the political imaginary, the essays then analyse the emplotment of history in visual culture, museum exhibitions, drama, and the fa brication of national identities, culminating in some case studies of literary recreations of history, which suggest that the ultimate source of historiographic transformation is related to writing itself as a performative act. The overall argument therefore drifts from radical antirepresentationalism to an emphasis on presentation over representation, and from there to the performativity of the historical text.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.019 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".