Bibliographic record
Abstract
Marginalized communities use, adapt, and produce architectures in hinterland spaces in response to geographical, environmental, social, nationalist, and other political forces. Scholarly discourse and approaches to architectural practice may likewise be formed and coerced through marginalization. The hinterland, as the outlying territory beyond the urban or geographical centre, is the physical manifestation of these forces that shape the social margins. At times, architecture is itself a marginalizing actor, and at others, it becomes the site of resistance and negotiation, providing spatial agency and autonomy, and facilitating distributive justice in regard to services and resources. In the hinterland, new architectures are created, pre-existing spaces are destroyed and re-made, and movement, change, and adaptation are given momentum. This article introduces the special issue on hinterland forces. I categorize architectural responses, both in architecture made and used by those in power to control marginal populations, and created by and for marginalized people. This is followed by a summary of the multi-field perspectives and scholarly methods of the contributing authors. The discussion focuses on architectural matters relevant to Islamic societies in several global regions, but the socio-spatial questions and associated responsibilities are relevant to practitioners and scholars in all architectural fields.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.019 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".