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Record W2561145192

Rethinking Roman perceptions of coastal landscapes : a case-study of the Levant

2016· dissertation· en· W2561145192 on OpenAlexfundno aff
Carmen Obied

Bibliographic record

VenueePrints Soton (University of Southampton) · 2016
Typedissertation
Languageen
FieldArts and Humanities
TopicMaritime and Coastal Archaeology
Canadian institutionsnot available
FundersHumanities Research Group, University of WindsorUniversity of CyprusDirectorate for Mathematical and Physical SciencesAarhus UniversitetUniversity of WindsorTechnion-Israel Institute of TechnologyUniversity of Haifa
KeywordsSeascapeGeographyContext (archaeology)PerceptionArchaeologyGeospatial analysisField (mathematics)Representation (politics)Historical geographyPoliticsCartographyHistoryHuman geographyEpistemologyEcology
DOInot available

Abstract

fetched live from OpenAlex

A recent resurgence of interest in the field of ancient geography and navigation has led to a need to re-evaluate the surviving corpus of ancient texts and archaeological evidence to seek alternative modes of perceiving space in the past. Links can be traced between ancient mariners’ practical experience and geographers’ conceptualisation of space, which present a complex ‘jigsaw puzzle’ of the oikoumene (known inhabited world). This research thus presents a case-study of the Levantine coast and explores alternative modes of perceiving space beyond the predominant linear approach. This is achieved through a comparative analysis of selected ancient sources, focusing on maritime archaeological evidence and geospatial analysis. The prime objective is to demonstrate the diverse nature and approaches of ancient authors’ representation of the oikoumene, as a means of conceptualising spatial associations and navigating the seascape. This is investigated through two key themes that emerged in the data: (A) ‘Static’ and (B) ‘Movement’, within a multidisciplinary framework set in the Roman Levant. A “common sense geography” approach is adopted, in which themes are considered and explored through different conceptual models, particularly in the context of sailing practicalities and mariners’ practical experience, as a means of providing insights into which authors experienced the described voyages or had a sense of seafaring. It raises questions on the nature of their sources, genres and purpose, underlining the relation between political and geographic knowledge. Understanding how these factors reflect on ancient notions of navigation can help to improve our knowledge of past perceptions of the maritime landscape and the dynamic relationship between people and the sea. The Levant region presents a high degree of variation, both physically and conceptually. Aspects linked to the nature and scale of navigation are examined in relation to regional maritime conditions, harbours, activities and routes. These themes are further contextualised via analogous cases in other regions of the Eastern Mediterranean. Emerging patterns offer insights into which authors actually experienced these voyages, as well as raising questions relating to the nature of their sources, genres and purpose. Results reflect a varied sense of spatial awareness of the known world amidst ancient authors, suggesting more multi-faceted ways of perceiving space in antiquity, and thus, improving our knowledge of past perceptions of the maritime landscape and the dynamic relationship between people and the sea, from both a mariner’s and armchair geographer’s perspective.

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)0.006
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0150.010
Scholarly communication0.0060.005
Open science0.0030.006
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.018
GPT teacher head0.207
Teacher spread0.189 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2016
Admission routes1
Has abstractyes

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