Bibliographic record
Abstract
It was the purpose of this survey to determine what use has been made of psychometric tests in the nursing field and to ascertain how widely this method has been accepted for selection and guidance in the training schools of the United States and Canada. Information regarding the use of tests in the field of nursing in the United States was obtained from the accumulation of literature on the subject and by writing directly to various workers in the field. A detailed survey was made by correspondence of Canadian schools of nursing to determine what use is being made of psychometric tests in the selection of their candidates and the counseling of their trainees. Data were obtained from the Canadian Nurses Association.regarding the rate of withdrawal and the reasons for withdrawal in Canadian training centres. Certain additional information was obtained with regard to the status of testing in English schools of nursing. The collected data were reviewed, analyzed and the salient features noted. The value of psychometric testing to Canadian schools of nursing has been considered. The results of this study regarding the value of psychometic selection methods to Canadian schools of nursing are not conclusive. Although 79% of American schools of nursing employ psychometric selection techniques, the rate of elimination of nursing students in 1947 was 39%. In Canada, where scientific selection methods have been virtually non-existent, the elimination rate was only 20% in 1948. It is doubted that any of the available testing devices could appreciably reduce this figure. It is concluded, however, that testing devices might be used to advantage for the guidance and counseling of nursing students in Canadian training centres and that test batteries might be employed in selection in those areas where the elimination rate appears to be abnormally high.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".