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Record W2321384695 · doi:10.1515/islam-2015-0006

Town and Steppe in Ottoman Syria: Hostility, Exploitation and Cooperation in the Late Seventeenth and Eighteenth Centuries

2015· article· en· W2321384695 on OpenAlexaff
James Reilly

Bibliographic record

VenueDer Islam · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicIslamic Studies and History
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsHostilitySteppeEconomic JusticeHistoryPolitical scienceSociologyLawArchaeologyPsychologySocial psychology

Abstract

fetched live from OpenAlex

Abstract Late-seventeenth- and eighteenth-century sources from the Homs and Hama region in Ottoman Syria present contrasting portrayals of Bedouins. Taken together, these sources offer conflicting perspectives with respect to relationships between peoples of the towns and the steppe. On the one hand, literary sources typically portray Bedouins as antitheses of urban life, as savage wanderers who lived outside the norms of propriety and who collectively posed a threat to the wellbeing and property of settled people and of travelers. But on the other hand, legal sources portray Bedouins variously as targets of exploitation or taxation by urban-based governments; or as partners with urban people in contractual undertakings; or as imperial subjects who, like any others, would seek justice in the urban Sharīʿa courts. The article explores these differing characterizations, and seeks to explain the multifarious realities that different sources convey. It concludes by suggesting that relationships between town and steppe were on their way to becoming more institutionalized in the last years of the eighteenth century. This development foreshadowed documented nineteenth-century trends in which urban civil norms and institutions became noticeable in the lives of Bedouins who lived in proximity to towns and urban centers.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.010
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.033
GPT teacher head0.284
Teacher spread0.251 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations2
Published2015
Admission routes1
Has abstractyes

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