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Record W1959756549

Initiating New Community and Field Education Partnerships: The Congregational Social Work Education Initiative

2015· article· en· W1959756549 on OpenAlexvenueno aff
Wayne Moore, Jay Poole, F. B. Pearson, Lelia Moore, John C. Rife

Bibliographic record

VenueCanadian social science · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsnot available
Fundersnot available
KeywordsInternshipWork (physics)SociologySocial workField (mathematics)Public relationsPolitical scienceManagementPublic administrationEngineeringLaw
DOInot available

Abstract

fetched live from OpenAlex

At the start of a new academic year in August 2007, the Joint Master of Social Work Program in Greensboro, North Carolina, launched a new field education venture – The Congregational Social Work Education Initiative (CSWEI).  North Carolina Agricultural & Technical State University (NCA&TSU) and the University of North Carolina at Greensboro (UNCG) created and operate a single master of social work program which opened in 1997.  The universities have a rich history of cooperation with managing a joint undergraduate social work internship program since 1978. The Council on Social Work Education has identified that field education as the signature pedagogy for social work education.  The success of any field education experience is dependent upon having students complete their field education experience within community- based programs and services.   However, such training opportunities have changed, which has placed more pressure in locating quality field educational sites or in the development of new models.

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)0.018
metaresearch head score (Gemma)0.012
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 score0.019
Threshold uncertainty score0.093

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.012
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0120.006
Scholarly communication0.0080.006
Open science0.0030.020
Research integrity0.0050.009
Insufficient payload (model declined to judge)0.0190.002

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 head0.216
GPT teacher head0.421
Teacher spread0.205 · 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

Citations2
Published2015
Admission routes1
Has abstractyes

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