A review of activity recording systems in community health nursing
Bibliographic record
Abstract
The purpose of this study is to evaluate the role of activity data in the management of community health nursing services. The study begins by examining what community health nurses do. Particular attention is given to the management structure in community health nursing. The kinds of information that individuals at different levels in the organization of community health nursing require, are investigated. One of these kinds of information is activity data. Thus, the role that activity data can play for those at each organizational level is explored. Various factors that can influence the usefulness of activity data are examined. The conceptual and functional features of six provincial and one federal activity recording system are analyzed. This is followed by a more detailed study of a particular system, the Alberta Community Nursing Activities Recording System. In reviewing the systems analyzed, the study finds that a common model for activity recording systems cannot be derived. Objectives are found to be so vaguely defined that the evaluation of an activity recording system is forced to rely largely on the subjective feelings of the systems users. Having examined some perceived alternatives to current systems, it is felt that a thorough revision of presently operating systems should be undertaken.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.012 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".