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Record W7070885553

The Role of Condominium Amenities in Community Building

2020· other· en· W7070885553 on OpenAlexaboutno aff

Bibliographic record

VenueYorkSpace (York University) · 2020
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsNucleofectionHyporeflexiaTSG101Articular cartilage damageCircumstantial evidenceFusible alloy
DOInot available

Abstract

fetched live from OpenAlex

Many Canadian cities are facing densification through the condominium-boom. Planning policies and neoliberalism are encouraging this form of housing. The term “community” is recognized in legal and land-use planning processes through a political lens, but it does not consider the sociological aspect. Residents make the community by developing relationships. Research is needed to identify if residents enjoy their condo amenities and if they feel it has an impact on community building. By researching this matter, planners, policy makers and condo board members can make certain changes that may improve the residents’ sense of community. This study consists of a mixed methods approach: quantitative and qualitative. Data on condo amenities has been collected from a real estate website, for data on an inner city (Downtown Toronto), an older suburb (Scarborough) and a new suburb (Vaughan). This provides data on the types of amenities available to condo residents. Residents from these areas also described their experiences. Both of these methods inform the condo residents’ perspectives. As there is a rise of feeling lonely in today’s society, cities need to plan for the psychological wellbeing of inhabitants. The narratives of cities are changing, which means that definitions of community are also changing. It is important to make structures that satisfy the psychological and physical needs of residents.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.241
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.201
Teacher spread0.188 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2020
Admission routes1
Has abstractyes

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