(RE)FRAMING SPATIALITY AS A SOCIO-CULTURAL PARADIGM: EXAMINING THE IRANIAN HOUSING CULTURE AND PROCESSES
Bibliographic record
Abstract
With rapid changes in urban living today, peoples’ behavioural patterns and spatial practices undergo a constant process of adaptation and negotiation. Using “house” as a laboratory and everyday life and spatial relations of residents as a framework of analysis, the paper examines the spatial planning concepts in traditional and contemporary Iranian architecture and the associated socio-cultural practices. Discussions are drawn upon from a pilot study conducted in the city of Kerman, to investigate ways in which contemporary housing solutions can better cater to the continually changing socio-cultural lifestyles of residents. Data collection for the study involved a series of participatory workshops and employed creative visual research methods, participant observation and semi structured interviews to examine the interlacing of everyday socio-spatial relations and changing perception of identity, belonging, socio-cultural and religious values and conflict. The inferences from the study showcases the emerging social and cultural needs and practices of people manifested through the complex relationship between residents, the places in which they live, and its spatial planning and organisation. For a better understanding of this complex relationship, the paper argues the need for resituating spatiality as a socio-cultural paradigm.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.024 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| 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".