MétaCan
Menu
Back to cohort
Record W4402672503 · doi:10.31857/s2686673024010098

The Annual Canadian Sociological Association Conference 2023. Research Cluster: Sociology of Housing

2024· article· en· W4402672503 on OpenAlexaboutno aff
Denis Litvintsev

Bibliographic record

VenueUSA & Canada Economics – Politics – Culture · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicUrbanization and City Planning
Canadian institutionsnot available
Fundersnot available
KeywordsSociologyAssociation (psychology)Cluster (spacecraft)Social scienceRegional scienceEpistemologyPhilosophyComputer science

Abstract

fetched live from OpenAlex

From May 29 to June 2, 2023, the Annual Conference of the Canadian Sociological Association was held at York University in Toronto, where various academic, research, educational, and administrative topics were discussed. The conference was part of the Congress of the Canadian Federation for the Humanities and Social Sciences and attracted speakers and attendees from Canada and other countries. Notably, for the first time since 2003, a research cluster focusing on the sociology of housing was presented, which had been initiated within the association at the end of 2021. Participants included scientific and pedagogical professionals, students, practitioners, and independent researchers, who engaged in two sections dedicated to sociological studies of housing and homelessness. Discussions covered a range of topics including chronic homelessness among women, mobile homelessness, the risk of homelessness among youth, attitudes towards the homeless, housing conditions of different social groups, and housing precarity. Special attention was given to state housing policy and the federal 'Housing First' strategy, the outcomes of which are subject to debate. The reports presented by the Sociology of Housing Research Cluster are of great interest to researchers focusing on housing issues in liberal democratic countries, including Canada, and to sociologists interested in developing housing sociology in Russia based on international experiences.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.653
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.050
GPT teacher head0.324
Teacher spread0.274 · 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
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
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueUSA & Canada Economics – Politics – CultureSame topicUrbanization and City PlanningFrench-language works237,207