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Record W2569442755 · doi:10.1093/jis/etw065

<i>The Byzantine–Islamic Transition in Palestine: An Archaeological Approach</i> By Gideon Avni

2016· article· en· W2569442755 on OpenAlexaff
Marcus Milwright

Bibliographic record

VenueJournal of Islamic Studies · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicArchaeology and Historical Studies
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsByzantine architectureIslamContext (archaeology)HistoryChronologyArchaeologyArchaeological recordAncient historyExcavationPalestinePeriod (music)Privilege (computing)ArtLawPolitical science

Abstract

fetched live from OpenAlex

The Arab conquests of the seventh and early eighth centuries had a profound impact on the history of Eurasia. While debate will continue over the dates of specific battles and the capitulations of given towns and cities, there is broad agreement over the fundamental chronology leading to the establishment of a massive new empire stretching from the Atlantic coast to the border with Tang dynasty China. Scholars have long recognized the potential of archaeology to contribute to the questions surrounding the demographic, economic and cultural shifts that occurred during this crucial period. Attempts to exploit the material record have often stumbled, however, due to the widespread tendency to privilege textual claims over archaeological data, the existence of considerable lacunae in the record of excavations and field surveys, and the imprecise or erroneous dating of buildings and portable objects, particularly ceramics. There have been attempts in recent years to offer critical appreciations of archaeological discoveries. Most notable in the present context is Alan Walmsley’s short, but perceptive, Early Islamic Syria: An Archaeological Assessment (Duckworth, 2007). Gideon Avni’s new book takes a similar trajectory, but limits itself largely to the region of historical Palestine in the transition from Byzantine to Islamic rule. While the geographical range of this new study is smaller, the reader is more than compensated by the depth of the analysis. Avni takes advantage of the intensity of archaeological activity in Israel (ranging from long-term projects to rescue excavations and surveys) in order to examine the changes that occurred in urban and rural areas from the fourth to the eleventh centuries.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.343
Threshold uncertainty score0.855

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.036
GPT teacher head0.251
Teacher spread0.216 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2016
Admission routes1
Has abstractyes

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