The 19th century olive oil industry in Ayvalik and its impact on the settlement pattern
Bibliographic record
Abstract
Ayvalık which is located on the Aegean coast of the West Anatolia made its main breakthrough in the 19th century and owe this development to olive oil production which was the main economic input of the settlement since the establishment of Ayvalık. Ayvalık was within the hinterland of İzmir which was gained importance as a regional trade centre in the 19th century. Thus, Ayvalık found the way to improve its trade relations in an international level and eventually increase its olive oil production volume due to the growing demands. The new form of olive oil production; factories, developed together with the traditional house and workshop productions in the last quarter of the 19th century in Ayvalık. These three forms of production made up the second significant usage within the Ayvalık after the residential areas. The two or more floored, large volumed buildings were especially located on the shore, near to the port and trade facilities, on a flat terrain and became the most dominant and attractive buildings of the settlement. Besides the impressive industrial buildings, olive oil production itself effected the settlement pattern of Ayvalık. The main transportation axes were formed accordingly to the relationship between raw material areas and production places. The olive oil production also has an effect on the physical development direction of the settlement. The areas influenced from the negative effects of the production i.e., smell and dust were not chosen for development. The development of industrial buildings also blocked the physical relationship between the residential areas and sea. The industrial buildings such as factories, workshops and warehouses along the coast line reflect the industrial character of Ayvalık in the settlement’s silhouette.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
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".