Toward a Model for Effectiveness
Bibliographic record
Abstract
Effectiveness is difficult to define or measure, but is frequently associated with cost. A two phase study conducted with occupational health nurses in Alberta, Canada resulted in a beginning model for effectiveness. In 1997, Phase One of an exploratory descriptive study focused on physical assessment by occupational health nurses (N = 137) and perceptions of effectiveness in practice (n = 104). In 2001, Phase Two used focus groups (n = 7) to determine occupational health nurses' reactions to the preliminary analysis of questionnaire responses on effectiveness. The focus groups confirmed and expanded categories, and reconfigured the developing model. The model makes explicit the foundations, functions, relationships, and goals for effectiveness in occupational health nursing practice. The foundation includes registered nurse (RN) experience and baseline competence comprising occupational health nursing education, RN and occupational health nurse experience, and multidisciplinary knowledge. Ten specific functions and nine relationships describe the occupational health nursing specialty practice and promote achievement of five goals: balance, communication, continuing competence, leadership, and trust. The goal of balance needs articulation in the nursing literature.
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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 | 0.066 | 0.057 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.010 | 0.004 |
| Science and technology studies | 0.005 | 0.046 |
| Scholarly communication | 0.021 | 0.030 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.008 | 0.015 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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.
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".