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Record W4241596987 · doi:10.32920/ryerson.14663514

Architecture of memory

2021· preprint· en· W4241596987 on OpenAlexaff
Zohra Akbari

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldArts and Humanities
TopicCultural Heritage Management and Preservation
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsPalimpsestArchitectureCollective memoryIdentity (music)Computer scienceAestheticsHistorySociologyCognitive sciencePolitical sciencePsychologyArchaeologyArtLaw

Abstract

fetched live from OpenAlex

Buildings and city forms are restructured and reused through time in response to evolving contexts, with each successive change leaving traces of the past that accumulate as layers. Collective knowledge and memory are strongly tied to these artifacts, which provide the depth and continuity necessary for the affirmation of identity. Dramatic changes in the contemporary city have prompted a reconsideration of the way architecture adapts, and highlights the need for a creative approach to change and advancement. A successful approach would meaningfully engage the past and memory to record and transmit vital aspects of culture and history while simultaneously using them to inform future actions. The palimpsest as an evolving record provides a productive framework for this kind of transformation, and uncovers the tangible and intangible layers of a site to protect and project the future layers.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.021
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.014
Scholarly communication0.0120.009
Open science0.0010.005
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0210.003

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 head0.113
GPT teacher head0.236
Teacher spread0.124 · 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 designTheoretical or conceptual
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
Published2021
Admission routes1
Has abstractyes

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