A Positive Prognosis for the Future of the Learning Environment: Designing Schools for Children in Shinabad, Iran
Bibliographic record
Abstract
From 2004 to 2012, Iran experienced six large school fires that led to 51 injuries and five deaths.Unfortunately, such injuries were unavoidable in Iran due to the lack of proper facilities and poor living conditions, particularly in rural areas.The tragedy of these injured kids inspired me to improve the conditions of learning for children living in rural conditions in Iran.More specifically, the recent tragedy that occurred in Piranshahr County lead me to choose this site and create a design proposal for a new school in this community.Although what I offer here is a prototype, it is hoped that it might serve as a model for improving safety standards in communities that have faced similar tragedies.I am addressing the problems to this community due to the typical school setting for Iran's rural condition.Some of the ways in which architecture and design can help to ensure a positive prognosis for the future of learning environments in Iran is to create buildings that are good for both body and mind.Thus, this project aims to foster student learning and well being through architecture.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".