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Record W2063222394 · doi:10.5430/jnep.v2n4p154

Academic-service collaboration in evidence-based practice

2012· article· en· W2063222394 on OpenAlexvenueno aff
Susan Diemert Moch, Rebecka Harper, Angela Grimley, Brittney Castleman Thyssen, Teresa A. Coughlin, Paul Schedler, Megan Behl, Rachel Philipps

Bibliographic record

VenueJournal of Nursing Education and Practice · 2012
Typearticle
Languageen
FieldHealth Professions
TopicHealth Sciences Research and Education
Canadian institutionsnot available
FundersUniversity of Wisconsin-Eau Claire
KeywordsAgency (philosophy)Service (business)Medical educationProcess (computing)Evidence-based practicePsychologyMedicineComputer scienceBusinessSociologyAlternative medicine

Abstract

fetched live from OpenAlex

Through this academic-service collaboration, undergraduate students engaged with a service partner to complete evidence-based practice projects. This case report describes the process and the outcomes of the three year experience. Project outcomes were evaluated through student and staff surveys. Students completed pre- and post-project surveys that revealed increased knowledge of evidence-based practice (EBP) and increased confidence in finding evidence for practice. Student responses also indicated high satisfaction with the process. The service partner staff post-project surveys indicated a high level of satisfaction with the process, increased learning and that targeted agency outcomes had been achieved.

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)0.032
metaresearch head score (Gemma)0.057
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.169

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0320.057
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0090.004
Scholarly communication0.0080.004
Open science0.0030.022
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0150.005

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 head0.436
GPT teacher head0.662
Teacher spread0.225 · 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 designQualitative
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
Published2012
Admission routes1
Has abstractyes

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