MétaCan
Menu
Back to cohort
Record W2315002929 · doi:10.1177/0042098016639010

Witnessing urban change: Insights from informal recyclers in Vancouver, BC

2016· article· en· W2315002929 on OpenAlexafffundabout
Kate Parizeau

Bibliographic record

VenueUrban Studies · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Planning and Governance
Canadian institutionsUniversity of Guelph
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsGentrificationNeighbourhood (mathematics)DowntownRedevelopmentPovertySociologySpace (punctuation)Economic growthGeographyPolitical scienceEconomics

Abstract

fetched live from OpenAlex

The perspectives of those most affected by urban change are often understudied, although these voices have the potential to inform academic understandings of the production of gentrified space. The Downtown Eastside (DTES) neighbourhood of Vancouver, BC is undergoing a period of intense redevelopment, raising concerns about the potential displacement of its predominantly low-income residents. In this study, informal recyclers (people who earn income from collecting recyclable or resaleable items) share their observations of neighbourhood change based on their lives and work in the DTES. Informal recyclers’ observations reveal that diverse gentrifying processes are at play in the DTES, including restricted access to space, the social exclusion of othered bodies, and the symbolic construction of the DTES as a place of poverty that is in need of intervention. The inclusion of informal recyclers’ perspectives provides nuance to place-based processes of gentrification, and acknowledges the concerns of low-income urbanites most affected by urban change.

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)0.002
metaresearch head score (Gemma)0.004
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.284
Threshold uncertainty score0.571

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0240.010
Scholarly communication0.0070.002
Open science0.0020.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.064
GPT teacher head0.308
Teacher spread0.244 · 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

Citations17
Published2016
Admission routes3
Has abstractyes

Explore more

Same venueUrban StudiesSame topicUrban Planning and GovernanceFrench-language works237,207