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Record W4285478715 · doi:10.51952/9781447352570.ch008

Suburban community vignette

2021· book-chapter· fr· W4285478715 on OpenAlexaboutno aff
Candace Skrapek, Elliot Paus Jenssen

Bibliographic record

VenuePolicy Press eBooks · 2021
Typebook-chapter
Languagefr
FieldSocial Sciences
TopicClimate Change, Adaptation, Migration
Canadian institutionsnot available
Fundersnot available
KeywordsVignetteGeographyPsychologySocial psychology

Abstract

fetched live from OpenAlex

Situated in the middle of Canada’s prairie region, Saskatoon is the largest city in the province of Saskatchewan. Nestled on the meandering South Saskatchewan River, Saskatoon has many natural features that make it an attractive place to call home. The warm, long summer days, green, clean spaces, and a variety of social and cultural events contribute to active living, social engagement, and community participation. Saskatoon offers safe, friendly neighbourhoods, a variety of housing options, excellent educational opportunities, public and accessible transit services, increasingly accessible buildings and services, and a range of health and community services. Winter poses challenges for all residents, especially older adults who face safety issues related to icy and cold conditions and resulting in reduced opportunities for social connectedness. The 2016 Canadian Census lists the population of Saskatoon’s Census Metropolitan Area (CMA) as 295,095, 10.9% of whom are Indigenous people. The CMA’s population grew 12.5% between 2011 and 2016 – far outpacing the national growth rate of 5%. Population growth was due primarily to immigration related to Saskatoon’s rapid economic expansion. Like most cities in Canada, Saskatoon has grown outward from its historic core into mixed-development suburbs. Most older adults live in these car-dependent communities. Saskatoon’s Nutana Suburban Centre has the highest density of seniors in Canada. This model of suburban development poses many challenges for citizens as they age, often forcing unwanted moves in order to access needed supports and services. In 2016, 13.5% of the Saskatoon population was age 65 or older. The older adult population is culturally and socially diverse and consists of multiple generations with vastly differing characteristics, needs, and resources.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.970
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.326
GPT teacher head0.365
Teacher spread0.039 · 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
Published2021
Admission routes1
Has abstractyes

Explore more

Same venuePolicy Press eBooksSame topicClimate Change, Adaptation, MigrationFrench-language works237,207