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The Oxford Handbook of Engineering and Technology in the Classical World

2016· article· en· W3211518921 on OpenAlexvenueno aff
John Peter Oleson, T. E. Rihll

Bibliographic record

VenueAestimatio Sources and Studies in the History of Science · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicHistorical Astronomy and Related Studies
Canadian institutionsnot available
Fundersnot available
KeywordsEngineeringEngineering ethicsLibrary scienceComputer science

Abstract

fetched live from OpenAlex

This book was designed 'to survey the role of technology in the Greek and Roman cultures and their respective technological accomplishments, from approximately the eighth century BC through the fifth century AD' [3].More specifically, contributors were asked to provide critical summaries of what the ancients achieved in particular areas, to chart the development of their technology in these cultures over the period in question, to consider the historiography of important issues in their area, and 'to help put an end to the myth of a 'technological blockage' in the classical cultures' [6].The book is not meant to be a compendium of all technological procedures, devices, and machines in the classical world [6]; but the title and size raise the expectation that it will serve as an introduction to the field as a whole, suitable both for undergraduate students and academics new to it.Generally that expectation is realized, though, as usual with this sort of volume, the level at which chapters are pitched varies considerably and some contributors stick to their brief better than others.To what extent does this volume achieve its three principal aims-to summarize what the ancients achieved, to explain how their technologies changed through antiquity, and to explode the myth of technological blockage?The answer turns out to be bound up with how far contributors have engaged with those aims.With 33 chapters over nearly 900 pages, this review would become inordinately long were every contribution to be discussed equally and therefore it, like the volume itself, will be selective in its coverage, though every contribution is acknowledged to some extent.My selection is based on the apparent relevance of the material to Aestimatio's principal audience, historians of science.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.999
Threshold uncertainty score0.111

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.006
Science and technology studies0.0010.004
Scholarly communication0.0050.005
Open science0.0010.001
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0330.010

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.

Opus teacher head0.016
GPT teacher head0.237
Teacher spread0.220 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreReview

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".

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Citations0
Published2016
Admission routes1
Has abstractno

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