Bibliographic record
Abstract
Since human beings have always been social creatures and have shown a tendency to be connected to their fellows, obtaining solutions to create a suitable context for this goal is one of the concerns of many intellectuals and thinkers in human science, sociology, urbanism and some other related domains.But considering the industrialization and mechanizing the life today and prevalence of virtual connections, social interactions and cultural communications are being reduced.The first step to solve this problem can be the existence of suitable and sufficient context or framework in cities and all human habitats.The method of this research has been descriptive-analytical and for gathering data, questionnaires have been used.The population includes 160 people in Rasht who have been randomly chosen among those who visited cultural centers, the passers-by and some people familiar with the customers and ceremonies of the area.The data have been analyzed in two stages, then the information from the questionnaire has been analyzed using SPSS and finally the result has been derived.The result shows that first the standardization test has been done on the variable by Kolmogorov-Smirnov which shows that the signification levels of all the variables are not standard and Spearman correlation test showed that all of the research hypotheses have been accepted including framework and urban spaces and using specific elements can help increasing social interactions.Architectural framework and urban spaces can help attracting visitors and transferring cultural concepts.Creating public spaces in metropolitan can turn into a context to increase public interactions.Therefore, what is obtained from this research is the impact on environment on creating and promoting the interaction among people and citizens.Locating and the existence of pavement, applying local and traditional architecture, the existence of open area and finally the existence of cultural centers along with interaction, association, the feeling of belonging and securing are the main findings of this survey and they are important in designing; so, what is being formed would be in line with the goal of project.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.949 | 0.950 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".