Indigenous architectural futures: Potentials for post-apocalyptic spatial speculation
Bibliographic record
Abstract
The representation and discussion of the future in architecture has remained almost exclusively within the realm of western science fiction (sf) where technological determinism, either utopian or dystopian, is the primary force for social and cultural change and adaptation. However, there are significant instances from outside of western industrialist sf traditions that offer immense opportunities for reconsidering the idea of ‘the future' in architecture. This essays posits the potential value of indigenous sf to enrich current architectural discourse, where ‘indigenous' does not necessitate a strictly backwards orientation towards ‘primitive' technologies and social organizations, which is often the case in architectural discussions of indigenous building and design, but is instead situated within the projected temporal territories often reserved for western-dominated visionaries. Such sf offers examples of post-futurist (the idea of linear time being underemphasized in indigenouscultures) and post-apocalyptic (the apocalypse for many North American indigenous groups being the arrival of Europeans) visions that offer indispensible diversity to our current capitalist trajectory. The essay focuses on three novels: D. L. Birchfield's Field of Honor, Zainab Amadahy's The Moons of Palmares, and Leslie Marmon Silko's Almanac of the Dead.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.066 |
| Scholarly communication | 0.010 | 0.013 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".