Ancient Pasts for Modern Audiences : Public Scholarship and the Mediterranean World
Bibliographic record
Abstract
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. 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. Ancient Pasts for Modern Audiences 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. 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.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.016 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 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".