MétaCan
Menu
Back to cohort
Record W2938221617 · doi:10.7202/1058481ar

CREATING A SPACE FOR INNOVATIVE TEACHING, LEARNING AND SERVICE DELIVERY

2019· article· en· W2938221617 on OpenAlexaffvenue
Jeff Karabanow, Cyndi Hall, Harriet Davies, Andrea Murphy, Piedad Martin-Calero, Sarah Oulton, Michelle Titus

Bibliographic record

VenueCanadian social work review · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicService-Learning and Community Engagement
Canadian institutionsDalhousie University
Fundersnot available
KeywordsSocial workGeneral partnershipSpace (punctuation)Government (linguistics)SociologyWork (physics)NursingPublic relationsMedical educationService-learningMedicinePedagogyPolitical scienceEngineering

Abstract

fetched live from OpenAlex

The School of Social Work Community Clinic opened its doors in June, 2014 in a donated space in a local parish hall. With very few resources initially the clinic now has its own rented space, serves a caseload of over 200 marginalized community members and has provided field placement experiences for over 75 BSW/MSW, pharmacy, psychology, nutrition, nursing, and occupational therapy students. In this article, we will highlight the steps we took to create and develop the Clinic with a social justice/anti-oppressive foundation, and the practice-teaching approaches we use with our students. We will also describe how we are integrating an interprofessional and community-university partnership culture in our day-to-day work with marginalized populations. This process will be described and discussed in relation to both interprofessional health education and the provision of relevant and meaningful services to clients. The community development techniques we used to develop our clinic and how we have been able to grow and expand will be highlighted. The partners we have established in government, the university, and the community that have contributed to a more sustainable future are also described.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.939
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.032
GPT teacher head0.322
Teacher spread0.290 · 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 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

Citations3
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueCanadian social work reviewSame topicService-Learning and Community EngagementFrench-language works237,207