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Record W4239087528 · doi:10.32920/ryerson.14655474.v1

Disrupting privatization: Enhancing Solo-cultural Interaction

2021· preprint· en· W4239087528 on OpenAlexaboutno aff
Adrain Man

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicCollaborative and Sustainable Housing Initiatives
Canadian institutionsnot available
Fundersnot available
KeywordsRecreationUrbanizationNeighbourhood (mathematics)Economic geographySociologyArchitectural engineeringBusinessEnvironmental planningGeographyEconomic growthPolitical scienceEngineeringEconomics

Abstract

fetched live from OpenAlex

As a product of rapid urbanization, residential developments are continuously proliferating in both density and scale. Driven by a capitalistic regime, Toronto's current high-density residential design is becoming homogenous in spatial planning and generating undistinctive spaces. With the existing programmatic configuration are internally and privately focused, these spaces lack the opportunity for community development and divers recreational amenities, transforming the dwelling to another urban Junkspace (non-place). By creating hybridized spaces that bridge private and public zones, this thesis proposes to generate spontaneous social activities and interactions within interstitial spaces. The new composed areas provide a dynamic living environment with direct access to shared recreational activities, integrated outdoor spaces, and creative community spaces, attracting an influx of users from the surrounding neighbourhood. Using strategies of shifting narratives, interstitial spaces, ambiguous voids, and integrated landscapes, the hybrid spaces reinvents the traditional monotony spaces and explores urban pluralism on both community and building level.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.475
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
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 head0.053
GPT teacher head0.398
Teacher spread0.345 · 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 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
Published2021
Admission routes1
Has abstractyes

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