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Record W394853814

Welcome and Introduction - 22nd Annual John K. Friesen Conference - Taboo Topics in Residential Care (2013)

2013· article· en· W394853814 on OpenAlexaboutno aff
Andrew Sixsmith

Bibliographic record

VenueSummit (Simon Fraser University) · 2013
Typearticle
Languageen
FieldHealth Professions
TopicSocial and Demographic Issues in Germany
Canadian institutionsnot available
Fundersnot available
KeywordsTabooPsychologySociologyAnthropology
DOInot available

Abstract

fetched live from OpenAlex

This video comprises the welcoming address by Dr. Andrew Sixsmith to the attendees of the 22nd Annual John K. Friesen Conference, "Taboo Topics in Residential Care," held MAY 27-28, 2013, Vancouver, BC.\n \nThe Simon Fraser University Gerontology Research Centre (GRC) and the associated Gerontology Department in cooperation with Fraser Health, the Public Guardian and Trustee of British Columbia, the Seniors’ Directorate, Ministry of Health, Province of British Columbia and Vancouver Coastal Health have brought together a group of Canadian experts in residential care policy, practice and research to address such difficult-to-deal-with issues as resident-resident aggression; theft and financial exploitation in institutional settings; alcohol, drug and tobacco use and abuse; sexuality; and dying and death. The conference will also discuss when it is and is not appropriate to use physical and/or chemical restraints and anti-psychotic medications. The conference also features a public lecture that will present a national perspective on elder abuse in Canada.\nThe objective of the conference is not just to raise awareness of these issues but also to identify steps that are or should be taken to safeguard the health, safety and well-being of residents of long term care facilities and those who care for them – both today and for the future.\n We also gratefully acknowledge a grant from the SFU Library's Scholarly Digitization Fund for videography and post-production editing.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.733
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.017
GPT teacher head0.280
Teacher spread0.263 · 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 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
Published2013
Admission routes1
Has abstractyes

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