Review of Sustainability of Social Memory on the Basis of Spaces in Atatürk’s Visits in Mersin
Bibliographic record
Abstract
Social memory is a phenomenon that connects the past of the society with the present, is concrete in spaces and structures, and is kneaded with culture.Because of the social memory's need for space, social memory; cannot be separated from society, space and culture.With this study, it is aimed to analyze the structures in Mersin, which Atatürk visited throughout her life, and which are in the memory of the city users.In the first part of the study; definitions and source research, which constitute the conceptual framework of the study, are included.Later, Atatürk's visits to Mersin were researched and the places that Atatürk used in these visits were determined in the written publications and in the books in which the oral interviews were published.The general characteristics, historical development and architectural features of these places-structures in the social memory have been examined.In these examinations, the current situation of the structures was determined and the interviews with the individuals focused on the effects of memory and reminiscence.Structures with characteristics of being a historical structure bear the traces of culture, social structure, life experiences, and life styles of previous periods.Ensuring the sustainability of these structures with characteristics of being a historical document by protecting them keeps the social memory alive.Thus, the sustainability of the social memory will be provided through spaces.At the same time, by documenting the architectural identity of the examined Krizmon Mansion, Silifke Tekir Farm, Silifke Atatürk House, Government House, Train Station, it is aimed to create a resource for the study to transfer it to the future.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| 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".