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Record W7101393584 · doi:10.1080/20507828.2025.2542641

Memory in the Walls: An Exploration of Temporality in the Architecture of Nyayo House

2025· article· en· W7101393584 on OpenAlexfundno aff

Bibliographic record

VenueArchitecture and Culture · 2025
Typearticle
Languageen
FieldEngineering
TopicArchitecture, Modernity, and Design
Canadian institutionsnot available
FundersSmuts Memorial Fund, University of CambridgeSocial Sciences and Humanities Research Council of Canada
KeywordsTemporalityArchitecture

Abstract

fetched live from OpenAlex

Crumbling in the basement of Nyayo House are former torture chambers where political dissidents were imprisoned by the Kenyan government between 1983 and 1993. Despite decades of memorial activism since a regime change, the basement of this active government tower in downtown Nairobi remains in a state of neglected ruin. This article explores how Nyayo House nonetheless functions as a memorial site, and aims to understand how the materiality of the former torture chambers might enable processes of justice unfolding today. Redressing a lack of scholarly attention to the materiality of memorial sites by balancing phenomenology with the new materialisms, I argue that the material qualities themselves – concrete scratches, rusting metal, and cracked tiles – enable visitors to Nyayo House to temporally situate supposedly “past” injustices as active in their presents. In so doing, they are better able to collectively engage with the specters of violence that continue to resonate 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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.018
Scholarly communication0.0070.007
Open science0.0010.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.025
GPT teacher head0.252
Teacher spread0.226 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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