An analysis of marketing strategies for the recruitmen of students into baccalaureate nursing programs in Ontario
Bibliographic record
Abstract
This thesis is a study about marketing strategies for the recruitment of students into baccalaureate nursing programs, within the context of the transition to the degree entry requirement for nursing practice and the new collaborative nursing degree programs in Ontario. Recruitment practices were examined in three Ontario universities that offer baccalaureate nursing education. Study findings pertain to the sequence of recruitment events, nature of participation from the baccalaureate nursing programs, processes for coordination between institutional and program divisions, enrollment objectives of the nursing programs, and some initial perspectives with respect to the impact of collaboration on student recruitment. This research has particular relevance for the nursing profession at the current time. The Canadian Nurses Association expressed concern regarding the future supply of nurses in A Statistical Picture of the Past, Present and Future of Registered Nurses in Canada (1997). Contributing factors to a projected severe shortage are the large number of predicted retirements, the increased health care demand due to an aging population, and the decreased applicant pools in the 1990s. The document Health Human Resources: A Preliminary Analysis of Nursing Personnel in Ontario (1998), prepared for the Ontario Ministry of Health Nursing Task Force, expressed the same concerns after in-depth analysis of the Ontario population, health services utilization, and health human resources. This study contributes to the recruitment literature by discussing issues pertaining to institutional strategy that have received limited scholarly attention and that are also relevant to other academic programs. The findings reveal that institutional promotion and recruitment have an important role in the achievement of qualified applicant pools and influencing applicants' decisions relating to university choice. Recruitment is organized and implemented primarily by the central liaison office, but that office also seeks participation from the academic units to most effectively promote the programs. Likewise, the School of Nursing cooperates with the institutional office by involving its faculty members and students in the recruitment function; however, there appears to be limited promotion that is initiated internally by the School of Nursing. This situation might change, however, if the collaborative degree nursing programs require more joint efforts between the universities and their college partners to attract sufficient numbers of qualified applicants to all program sites.
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 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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".