The unique financial situation of a Primary Reservist: Satisfaction with compensation and benefits and its impact on retention
Bibliographic record
Abstract
Introduction: Within the Canadian Primary Reserves (P Res), members can be employed in various classes of service, and they often balance simultaneous civilian and military employment. The aim of the current study was to examine P Res members’ reliance on their military income, their satisfaction with the compensation and benefits, and whether compensation and benefits was related to 5-year turnover intentions. Methods: A P Res Retention Survey was completed by 3,669 members. Participants reported their reliance on their military income, employment status, satisfaction with 11 aspects of P Res compensation and benefits, and 5-year turnover intentions. The data were weighted by key demographic variables. Results: Most members reported a reliance on their P Res income and had some satisfaction with their pay and benefits. General linear model analyses were conducted to examine differences in members’ satisfaction across classes of service. Results demonstrated that members employed full-time within the P Res were less satisfied with their rates of pay, while part-time members were less satisfied with the medical and dental benefits. Furthermore, an association was found between P Res members’ satisfaction with compensation and benefits and their 5-year turnover intentions. Discussion: Although members tend to rely on their military incomes, their satisfaction varied by the level of their P Res employment. The Canadian Armed Forces may consider tailoring its financial services to aid P Res members with their financial management.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".