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Record W2530890345

Arguments in the Streets Became More Frequent

2016· dissertation· en· W2530890345 on OpenAlexaboutno aff
Pawel Bednarek

Bibliographic record

VenueUWSpace (University of Waterloo) · 2016
Typedissertation
Languageen
FieldEngineering
TopicArchitecture, Modernity, and Design
Canadian institutionsnot available
Fundersnot available
KeywordsHistoryGeography
DOInot available

Abstract

fetched live from OpenAlex

Our contemporary societal condition is comprised of an involuntary association of humans to a system which prioritizes Authoritarianism, hierarchy, and capitalism. In other words this system supports a systemic or enforced inequality which favours and rewards the privileged few and disenfranchises and criminalizes the marginalized many. Architecture is complicit in this condition. This being said, I am motivated to change the way architecture operates. The best way to change the praxis of architecture to better address this negative condition is through the development of an anarchist architectural/spatial practice. This anarchist architecture is intended to be revolutionary as well as constructive and pragmatic. Anarchist architecture seeks to subvert the complicity of architecture to the above condition and strives to affect positive social change through a multiplicity of tactics. \nUsing Toronto as a subject, this thesis is an experiment in a constructive anarchist architectural praxis which manifests itself through the craft of archiving, critical détournement, and the development of new spatial conditions.

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)0.004
metaresearch head score (Gemma)0.012
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.035
Threshold uncertainty score0.118

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0090.019
Scholarly communication0.0130.012
Open science0.0010.005
Research integrity0.0050.009
Insufficient payload (model declined to judge)0.0350.005

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 head0.197
Teacher spread0.187 · 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
Published2016
Admission routes1
Has abstractyes

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