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Record W4249585763 · doi:10.32920/ryerson.14651664

Healing Neighbourhoods through Urban Acupuncture

2021· preprint· en· W4249585763 on OpenAlexaboutno aff
Jonathan P. Pascaris

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Public Health Policies and Epidemiology
Canadian institutionsnot available
Fundersnot available
KeywordsVitalityMetaphorArchitectureContext (archaeology)Psychological interventionSociologyBuilt environmentPublic relationsPsychologyGeographyPolitical scienceEngineeringCivil engineering

Abstract

fetched live from OpenAlex

Well-being is a holistic concept of human health, and it is inextricably linked to environment. Built landscapes that do not service real human needs can be extremely detrimental to the growth of community. In the context of Toronto, this is no more apparent than in suburban neighbourhoods where changing demographics have left a populati on with diverse and urgent needs, but in which homogenous and auto-centric built environments inhibit the informal socializati on that contribute to both individual and urban vitality. This thesis purports that architecture has a parti cularly important role in the future of such neighbourhoods because of its capacity to intensify program and create opportuniti es for people to comingle. Drawing upon the metaphor of therapeutic acupuncture, this thesis will explore the ways in which punctual interventions can activate places. Objectives of connectivity, hybridity and porosity will be explored as the means by which this activation can occur. Ultimately, this thesis aims to assert the importance of architecture in facilitating more holistic understandings of urban health.

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)0.001
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: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.005
Scholarly communication0.0030.002
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.049
GPT teacher head0.318
Teacher spread0.269 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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