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Record W2239694542 · doi:10.1300/j010v44n03_02

Does Difference Matter?

2007· article· en· W2239694542 on OpenAlexaffabout
Joanne Sulman, Marylin Kanee, Paulette Stewart, Diane Savage

Bibliographic record

VenueSocial Work in Health Care · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicGender Diversity and Inequality
Canadian institutionsMount Sinai Hospital
Fundersnot available
KeywordsDiversity (politics)Promotion (chess)Social workFocus groupWork (physics)Plan (archaeology)Cultural diversityNursingPublic relationsMedicineMedical educationPolitical scienceSociologyEngineeringGeography

Abstract

fetched live from OpenAlex

The urban hospital workplace is a dynamic environment that mirrors the cultural and social diversity of the modern city. This paper explores the literature relating to diversity in the workplace and then describes an urban Canadian teaching hospital's comprehensive approach to the promotion of an equitable and inclusive diverse environment. With this goal, four years ago the hospital established an office of Diversity and Human Rights staffed by a social worker. The office provides education, training, policy development and complaints management. The administration also convened a hospital-wide committee to advise on the outcomes, and to plan a process for diversity and human rights organizational change. The committee worked with a social work research consultant to design a qualitative focus group study, currently ongoing, to explore the perspectives of hospital staff. The lessons learned from the process have the potential to increase overall cultural competency of staff that can translate into more sensitive work with patients.

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)0.007
metaresearch head score (Gemma)0.028
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.028
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0070.019
Scholarly communication0.0070.009
Open science0.0010.004
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0210.002

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 head0.072
GPT teacher head0.360
Teacher spread0.288 · 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

Citations12
Published2007
Admission routes2
Has abstractyes

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