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Record W3015328332 · doi:10.5206/uwomj.v88i2.7303

Mental health system change

2020· article· en· W3015328332 on OpenAlexaffvenueabout
Meagan Wiederman, Celina Everling, Nathan Leili, Saba Shahab

Bibliographic record

VenueUniversity of Western Ontario Medical Journal · 2020
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsWestern University
Fundersnot available
KeywordsMental healthGeneral partnershipMental illnessEmpowermentNursingPsychologyInstallationPublic relationsMedicineBusinessPsychiatryEngineeringPolitical science

Abstract

fetched live from OpenAlex

Mental health is the psychological wellness of a person. Currently, mental health illnesses are treated by hospital and community. Due to the transition of this system from psychiatric institutes, the hospital and community are not necessarily well connected. It is essential that the hospital and community are connected since patients need to feel supported by their community at all stages of their recovery in order to make a network of wellness. In order to tackle the problem of connecting the hospital and community for the personal recovery of people with severe mental illness, my team, Re-MIND London, proposed an innovative solution suite, involving: a liaison between community and hospital; a shared menu of resources; information sharing through education and samplers; having patients engage on community outings; and providing peer mentor support. In installing this solution, we have re-kindled connection between Parkwood Institute for Mental Health and the Canadian Mental Health Association in London, ON, at an administrative level, as well as staffer and patient level. Patients report that they need to feel like they in the community to have hope towards a proper discharge plan. In installing sections of this innovative solution, our team learned self-empowerment to challenge the existing system, regardless of our position. We are connecting, at many levels, diverse individuals and organizations to leverage their strengths to form a strong and sustainable partnership that will insulate people with mental illness in a community throughout treatment.

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)0.004
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.086
Threshold uncertainty score0.289

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0050.002
Scholarly communication0.0050.003
Open science0.0020.007
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0860.007

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 head0.261
GPT teacher head0.365
Teacher spread0.104 · 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 designNot applicable
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
Published2020
Admission routes3
Has abstractyes

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