Commitment to the nursing profession: an exploration of factors which may explain its variability
Bibliographic record
Abstract
The purpose of the study was to determine factors which may explain variability in the degree of commitment to their profession among nurses in British Columbia. A common theme in the literature on commitment to nursing is that it is a powerful force which shapes a nurse's career. As such, it is the responsibility of the nursing profession to understand the nature of commitment. This in part can be accomplished by having knowledge about factors which explain variability in the commitment of nurses to their profession. Review of the literature revealed the factors to be personal and work-related. Based on the work of Alluto and Hrebiniak, a five-part questionnaire was pilot tested, then mailed to a stratified random sample of four hundred nurses living in the Greater Vancouver District. Of this number 256 (64%) were returned. The total number of usable questionnaires following, a process of elimination was 217 (54.2%). Data analysis took place in three stages. The principal findings were as follows. First, an analysis of the sub-tests revealed them to be internally consistent with the exception of the Professional Actions sub-test. The reliability estimates of the five sub-tests ranged from r = .93 to r = .52. Second, analysis of the demographic data revealed a sample closely resembling the population of interest. Third, a stepwise multiple regression analysis produced an R² of 23%. Four variables entered the regression equation. Of these, three were personal variables: professional orientation, marital status and basic education. The fourth, a work-related variable, was work satisfaction. Thus, it was found that certain personal and work-related variables did explain variability in commitment, accounting for 23% of the total , variability. This, however, leaves a large portion of the variability unexplained. Of the 77% remaining, 7% is due to random error (as indicated by the reliability estimate of the Commitment Index r = .93). In view of the findings in the present study and similar findings in the studies by Alluto and Hrebiniak, other untested variables which may explain variability in commitment need to be researched. In addition to new variables, a change in methodology using path analysis instead of the linear model is also recommended.
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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 | 0.009 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".