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Suburban community vignette

2021· book-chapter· en· W3143071837 on OpenAlexaboutno aff
Candace Skrapek, Elliot Paus Jenssen

Bibliographic record

VenuePolicy Press eBooks · 2021
Typebook-chapter
Languageen
FieldSocial Sciences
TopicMigration, Aging, and Tourism Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousVariety (cybernetics)GeographyVignetteSocial connectednessCensusResidenceCommunity engagementPopulationEnvironmental planningPolitical scienceSocioeconomicsPublic relationsSociologyEnvironmental healthMedicineEcologyPsychology

Abstract

fetched live from OpenAlex

This chapter highlights Saskatoon, the largest city in the province of Saskatchewan that is nestled on the meandering South Saskatchewan River and is considered to have many natural features that make it an attractive place to call home. The chapter describes warm, long summer days, green, clean spaces, and a variety of social and cultural events that contribute to active living, social engagement, and community participation. It also talks about the safe and friendly neighbourhoods of Saskatoon that offers a variety of housing options, excellent educational opportunities, public and accessible transit services, accessible buildings and services, and a range of health and community services. The chapter elaborates that winter poses challenges for all residents, especially older adults who face safety issues related to icy and cold conditions that result in reduced opportunities for social connectedness. It looks at the 2016 Canadian Census that lists the population of 295,095 residents, of which 10.9 percent are indigenous people.

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)0.000
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.233
Threshold uncertainty score0.781

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.001
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.2330.046

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 head0.082
GPT teacher head0.328
Teacher spread0.246 · 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
Published2021
Admission routes1
Has abstractyes

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Same venuePolicy Press eBooksSame topicMigration, Aging, and Tourism StudiesFrench-language works237,207