Motivation, sensation seeking, and the recruitment of volunteer firefighters
Bibliographic record
Abstract
Purpose – The purpose of this paper is to examine similarities and differences in motivational-type and sensation seeking tendencies in male and female firefighters and to determine how a growing focus on extrinsically focused reasons to volunteer relates to traditional, intrinsically focused rationales. Design/methodology/approach – In total, 160 volunteer firefighters (29 women, 131 men) were compared to 210 undergraduate controls (171 women, 39 men) across a spectrum of motivation and sensation seeking types in a cross-sectional, questionnaire-based, approach. Findings – Female volunteers showed a distinct pattern of motivations for volunteering and though similar to their male counterparts in Thrill and Adventure Seeking were lower in impulsive sensation seeking. Greater levels of career-focused motivation did not come at the cost of intrinsically focused motivation or to the number of years one projected volunteering. Research limitations/implications – The approach did not provide the means to check if reported intentions translate to behavioural outcomes and the small number of female firefighters sampled compromised power. Practical implications – Findings of how female volunteers differ from male counterparts and university women might be considered when developing recruitment drives and formulating policy to modify what is rewarded in firefighting. Findings further suggest that the potential of gaining paid employment is unlikely to compromise traditional reasons for volunteering. Social implications – Evidence that female volunteers possess a distinct and desirable pattern of motivations and sensation seeking relative to their male counterparts seemingly provides a rationale to target women in recruitment drives that extends beyond bolstering numbers. However, that they were also distinct from university females raises questions about their representativeness and, in turn, about the size of the potential pool from which fire services may draw. Hypothesized concern about the negative impact that volunteering as a means to obtain paid work has on more traditional, intrinsically focused motivations appears to be unfounded. Originality/value – Moves beyond anecdote to provide empirical evidence of the motivations and sensation seeking tendencies of volunteer firefighters, especially women, and contributes to a nascent area of inquiry about how intrinsic and extrinsic motivation can co-exist in this group.
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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 | 0.000 |
| 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".