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Record W2014015929 · doi:10.1177/1049731509335528

What Is Implementation Research?

2009· article· en· W2014015929 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueResearch on Social Work Practice · 2009
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPsychological interventionSocial workImplementation researchContext (archaeology)Systematic reviewManagement scienceEngineering ethicsComputer sciencePsychologyMEDLINEMedicineNursingPolitical science

Abstract

fetched live from OpenAlex

Despite the growing knowledge base on evidence-based practices in social work and medicine, there is a large gap between what is known and what is consistently done. Implementation research is the study of methods to promote the uptake of research findings into routine practice. In this article, we describe the rationale for implementation research and outline the concepts and effectiveness of its practices. Despite a large number of systematic reviews of implementation interventions, many of the fundamental questions regarding what approaches should be used in which settings for which problems remain unanswered. We go on to argue that future implementation studies should assess the context of practice and key features of interventions to better inform service quality improvement efforts.

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.

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)0.058
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.776
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0580.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.007
Science and technology studies0.0110.000
Scholarly communication0.0000.003
Open science0.0010.000
Research integrity0.0000.004
Insufficient payload (model declined to judge)0.0070.013

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 head0.920
GPT teacher head0.846
Teacher spread0.075 · 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