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Record W4245626407 · doi:10.32920/ryerson.14658159.v1

Changing demographics in Hamilton may leave the kids behind

2021· preprint· en· W4245626407 on OpenAlexaffabout
Michelle E. Diplock

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicHealthcare innovation and challenges
Canadian institutionsCarleton UniversityToronto Metropolitan University
Fundersnot available
KeywordsGentrificationDisconnectionDemographicsPovertyInner cityDowntownKey (lock)Face (sociological concept)SociologyGeographyEconomic growthSocioeconomicsPolitical scienceDemographySocial scienceEconomicsComputer scienceArchaeology

Abstract

fetched live from OpenAlex

This paper addresses the stark geographic disparity that youth in Hamilton face when trying to access services. There is a high number of youth services concentrated in the inner and lower city, but this does not seem poised to meet the changing demographics and needs of the city of Hamilton. Gentrification and community uplift have started in the lower city, and as such, having a majority of youth services located in the downtown presents a major form of disconnection. This is especially shown as youths living in poverty begin to be pushed out of the lower city and into the inner suburbs on top of the Niagara Escarpment—a place that is geographically cut off from the rest of the city. This paper examines these issues and presents recommendations, to help youth and the City of Hamilton address this disconnection as Hamilton experiences unprecedented growth and development, which may leave the youth behind. Key words: An article on social planning and youth programing in Hamilton, Ontario, used the key words: Hamilton; youth services; gentrification; access.

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)0.001
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 score0.080
Threshold uncertainty score0.161

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0100.003
Scholarly communication0.0030.001
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.001

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 head0.108
GPT teacher head0.404
Teacher spread0.295 · 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

Citations0
Published2021
Admission routes2
Has abstractyes

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