Bringing It All back Home: the Practical Visual Environments of Southeast European Tells
Bibliographic record
Abstract
This article attempts to further our understanding of tells in southeast Europe by considering their landscape context, where the research methodology comprises an innovative hybrid of modern landscape theory, and GIS-based visual analysis. TAG poster image Tell landscapes are explored through the detailed analysis of a group of case study tells located in the Romanian Plain, in southern Romania, dating to the fifth millennium BC. A visual, so-called phenomenological approach is adopted, but novel to this paradigm is the use of GIS as the prime tool with which to conduct visual research. GIS offers a convenient means to visualise and quantify visual parameters of landscape, but its formal nature also brings some rigour to phenomenological research, which has been criticised for lack of standard method. Viewshed tools are utilised in standard form, but also in enriched Higuchi and Directional forms. The temporal nature of tell settlements is explored through the generation of viewshed maps from different cultural levels of the mound. Results of the analysis are presented and common patterns in the dataset identified. Taking inspiration from the Heideggarian notion of dwelling, a generalised interpretive framework is forwarded. It is suggested that tells were located with respect to visual entities in the environment, and that the nature of the visibility tells us something of the lives of people dwelling on and around them. The article is derived from a lecture given at the Theoretical Archaeology Group conference, Manchester, December 2002. Keywords: landscape archaeology, GIS, viewshed analysis, tells, southeast Europe, phenomenology This article will particularly interest: * Researchers in Balkan prehistory * Archaeologists with an interest in tells * Anybody interested in using GIS as part of a visual study of landscape * Archaeologists with an interest in landscape theory Key points: * A critique of traditional approaches to the study of prehistoric tells * The integration of contemporary archaeological landscape theory and GIS-based visual methods * The implementation of Higuchi and Directional viewsheds * The introduction of temporality into site-based viewshed analysis * To argue that less specific, more holistic interpretive frameworks are required in order to accommodate results deriving from diverse case study topographies * How visual analysis informs our understanding of changes in settlement configuration in the river valleys of southern Romania in the fifth millennium BC
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.011 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".