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Record W4234005425 · doi:10.32920/ryerson.14663943.v1

“Tolerated” and non-status persons‟ access to mental health support services: a comparison between Toronto, Canada and Aachen, Germany

2021· preprint· en· W4234005425 on OpenAlexaffabout
Avery Toppan

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsToronto Metropolitan UniversityYork University
Fundersnot available
KeywordsMental healthService (business)Service providerWork (physics)PsychologyPublic relationsBusinessPolitical sciencePsychiatryEngineeringMarketing

Abstract

fetched live from OpenAlex

Using the theoretical framework of Identity Formation, this Major Research Paper (MRP) aims to explore the Post-national rights of “tolerated” or undocumented persons in Toronto and Aachen, and their access to necessary mental health services. The assumption is that the experiences of these groups are both traumatic and unique, often creating emotional, mental and physical stress. These forms of stress require various forms of treatment, from formal mental health evaluations, to informal group counselling or bonding with persons of similar experiences. This work takes three service providers in each city, discusses the perspectives and services available, and offers an analysis as to whether they provide the suitable and necessary care for “tolerated” or non-status persons. I will argue that social exclusion in the form of contestant enmity is utilized to deny full access to support services. Recent legal and policy changes in both countries will be accounted for, and recommendations given as to how the service providers and actors at the municipal level can move forward to provide the necessary services.

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)0.002
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 score0.053
Threshold uncertainty score0.383

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0060.003
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0000.001
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 head0.038
GPT teacher head0.374
Teacher spread0.336 · 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

Citations1
Published2021
Admission routes2
Has abstractyes

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