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Record W4410286613 · doi:10.1080/10464883.2025.2463299

Seven Hundred Thousand Adobe Blocks

2025· article· en· W4410286613 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Architectural Education · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicLanguage, Linguistics, Cultural Analysis
Canadian institutionsCarleton University
Fundersnot available
KeywordsAdobeComputer graphics (images)Computer scienceEngineeringArchitectural engineeringEngineering drawingArchaeologyVisual artsArtHistory

Abstract

fetched live from OpenAlex

This essay examines adobe block-making at the Poston concentration camps in Arizona, where Japanese Americans were forcibly incarcerated during World War II. Focusing on the spatial, material and social dimensions of adobe construction by incarcerated laborers, the text reveals how the use of local earth and diverted water from the Colorado River Indian Reservation reflects not only the extractive and carceral forces of imperialism, but also a form of resistance rooted in the landscape itself. At Poston, adobe block-making became a site of collective agency within the oppressive legacies governed by the Law of the River, which continues to dictate water rights and resource distribution across the southwestern US. The essay views architecture as a political act, considering adobe block-making as both a response to and a rejection of extraction-based design frameworks. By grounding built forms in the land and fostering solidarity among laborers, the adobe blocks challenge dominant architectural practices toward a reimagined relationship with the land—one based on reciprocity, ecological stewardship and an architecture beyond extraction—that counters the global imperial frameworks driving resource commodification and hegemonic power today.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.722
Threshold uncertainty score0.734

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.010
GPT teacher head0.265
Teacher spread0.255 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it