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Record W4252183433 · doi:10.32920/ryerson.14653905

Managing crisis and living in crisis: health & place, what separation? A holistic view of the community environment at Sherbourne and Dundas

2021· preprint· en· W4252183433 on OpenAlexaff
Stephanie Beausoleil

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsCollege of the North Atlantic
Fundersnot available
KeywordsMindsetDignityAgency (philosophy)MandateInstitutionalisationPower (physics)Neighbourhood (mathematics)NarrativeBuilt environmentPublic relationsSociologyPolitical scienceEngineeringSocial science

Abstract

fetched live from OpenAlex

A person’s environment greatly influences and informs their emotional health, wellbeing and ability to live with dignity and express agency. The Sherbourne and Dundas neighborhood presents a matrix of spaces entrenched with high levels of violence, incivilities and public health hazards. Currently, there are numerous institutions working within and surrounding this community all with a mandate to support the vulnerable and stigmatized who live here yet to date has not been actualized on any level at Sherbourne and Dundas. The environmental living conditions for the neighborhood and the participants of this study are quickly deteriorating putting everyone within and surrounding the area at increased risk Findings of this narrative study with three residents indicate that there to be a stronger balance between community and service user voice in developing and informing programming as well at determining who occupies space in their environment as ‘helpers ’and other structural and systemic representations which yield a great amount of power as brokers in this marginalized and vulnerable neighbourhood space. In doing so this community would be able to hold power accountable in this environment, disrupt the hybridization of institutionalization that is in effect in this space.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.389
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.008
Research integrity0.0000.004
Insufficient payload (model declined to judge)0.0010.000

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 head0.125
GPT teacher head0.439
Teacher spread0.314 · 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 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

Citations0
Published2021
Admission routes1
Has abstractyes

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