Ancient Pasts for Modern Audiences : Public Scholarship and the Mediterranean World
Bibliographic record
Abstract
<p>This volume brings together specialists from a broad demographic and professional range – academics, museum curators, students, and content creators – to discuss case studies, challenges, and potential future avenues for public scholarship on the history, archaeology, and cultures of the ancient Mediterranean, North Africa and Western Asia.</p><p>Together, the contributions promote the creation of inclusive methods of knowledge mobilisation and communication in public spheres across three main areas: cultural heritage, pedagogy and public-facing scholarship. These areas have all been directly affected by Eurocentric structures that have claimed ownership of ancient Mediterranean cultural heritage and have dictated how it has been taught in schools and communicated to the broader public. The volume is divided into three sections – Museums, Teaching and Learning, and Global and Local Projects – each addressing pressing challenges faced within these interrelated fields and offering ways for us to overcome the exclusionary narratives that plague them.</p><p><em>Ancient Pasts for Modern Audiences </em>provides an invaluable resource for those interested in public history, from academics to lay audiences, in the fields of Ancient Mediterranean, North African, and Western Asian Studies. The book also appeals to professionals and researchers whose interests lie in public-facing scholarship, pedagogy, digital humanities, decolonisation studies, museum studies and popular media.</p><p>The Open Access version of this book, available at http://www.taylorfrancis.com, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives (CC BY-NC-ND) 4.0 license.</p>
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.008 | 0.013 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.091 | 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; both teacher heads 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".