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Record W3213979579 · doi:10.32920/ryerson.14656149.v1

Hybritopia: Seeking An Architecture of Reconciliation

2021· preprint· en· W3213979579 on OpenAlexaff
Catalina Ardila Bernal

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicUrban Planning and Landscape Design
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsArchitectureCorporationEpitomeSpace (punctuation)Independence (probability theory)Sense of placeFoundation (evidence)Subject (documents)SociologyPolitical sciencePolitical economyEnvironmental ethicsGeographySocial scienceLawArchaeologyArt

Abstract

fetched live from OpenAlex

The rural landscape in the global south has become the subjectivation¹ of ruthless economies and the demand for detachment and independence has been building up since the time of Discovery. As contemporary colonization is slowly reaching a rupture point between the corporation and minorities, governments and locals, urban and rural, developed and developing, architecture can mitigate the impacts as an agent of reconciliation. A space designated for the revitalization of land degradation, not in the sense of making land fertile again, but from the standpoint of a new foundation of cultures, communities and traditions, and more importantly, a setting for celebrating rural human existence, from life to death and infinity. A sacred space, or a rural hybritopia, embodies the epitome of redemption, reconciliation and renewal for villages, towns, minorities and displaced communities. ¹The term was coined by Michel Foucault, and it is when the subject is analyzed through the relationships and circumstances of the real world rather than the inherent qualities of being (Rebughini, 2014)

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 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.151
Threshold uncertainty score0.999

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)0.0020.000

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 head0.017
GPT teacher head0.225
Teacher spread0.208 · 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 teacher head, not a consensus.

Study designObservational
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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