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Forensic nursing educational development: an integrated review of the literature

2010· review· en· W1961675600 on OpenAlexaff
Arlene Kent‐Wilkinson

Bibliographic record

VenueJournal of Psychiatric and Mental Health Nursing · 2010
Typereview
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsForensic nursingSpecialtyNursingCurriculumNurse educationMedicineNursing researchForensic psychiatryNursing practiceForensic scienceMedical educationPsychologyFamily medicinePsychiatryPedagogy

Abstract

fetched live from OpenAlex

Accessible summary The importance of this paper's findings are: Forensic nursing is a nursing specialty with subspecialties that focus on nursing practice who care for victims and offenders, living and deceased at the clinical legal interface. The gaps identified in the literature indicate where educational development did not occur concurrently with role development of forensic nursing. Role development occurred ahead of educational development for all subspecialty areas of forensic nursing except sexual assault nurse examiners, where it developed simultaneously. Forensic nursing formal education did not develop sooner as infrastructures were not in place to support it. Abstract The forensic area of practice has been a popular career choice and area of study for many of the health science disciplines. Forensic nursing is a nursing specialty with subspecialties that focus on nursing practice who care for victims and offenders, living and deceased at the clinical legal interface. This integrated review of the literature overviewed the historical development of each of the forensic nursing subspecialties and identified gaps in specialty nursing educational development. Although multiple studies for the last 30 years identified the need for forensic nursing education, recommendations did not soon translate into educational curriculum development. The literature showed that role development was not concurrent with educational development in all forensic nursing subspecialties.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.976
Threshold uncertainty score0.883

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.030
GPT teacher head0.428
Teacher spread0.399 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreReview

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

Citations57
Published2010
Admission routes1
Has abstractyes

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