MétaCan
Menu
Back to cohort
Record W2900734302 · doi:10.1111/tesg.12338

Neighbourhood Change and the Fate of Rooming Houses

2018· article· en· W2900734302 on OpenAlexafffundabout
Jill L. Grant, Uytae Lee, Janelle Derksen, Howard Ramos

Bibliographic record

VenueTijdschrift voor Economische en Sociale Geografie · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing, Finance, and Neoliberalism
Canadian institutionsGovernment of Northwest TerritoriesDalhousie University
FundersSocial Sciences and Humanities Research Council of CanadaUniversity of TorontoDalhousie University
KeywordsGentrificationDisadvantagedNeighbourhood (mathematics)Investment (military)Low incomeAffordable housingBusinessPopulationEconomic growthLow income housingEconomicsDemographic economicsPolitical scienceSociology

Abstract

fetched live from OpenAlex

Abstract The paper examines changes in the number and geography of rooming houses in Halifax, Canada. Several factors contributed to the near extinction of private single‐room accommodations for hard‐to‐house, low‐income adults between 1995 and 2016, while student‐oriented rooming properties increased. Economic and population growth created strong housing demand as low borrowing costs facilitated property investment in central neighbourhoods. Planning policies encouraged greater densities and heights in areas formerly accommodating low‐rent rooming houses, while regulations held rooming houses to new standards. Cultural preferences for urban living accelerated demand for, and costs in central areas. Together these factors contributed to an apparent rent gap that made many rooming house properties ripe for transformation, contributing to diminished shelter opportunities for disadvantaged low‐income residents. The case illustrates how gentrification extinguishes some market‐provided low‐income housing options.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.629
Threshold uncertainty score0.747

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.036
GPT teacher head0.228
Teacher spread0.192 · 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 designObservational
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

Citations4
Published2018
Admission routes3
Has abstractyes

Explore more

Same venueTijdschrift voor Economische en Sociale GeografieSame topicHousing, Finance, and NeoliberalismFrench-language works237,207