A response to the Vancouver call for action: addressing the needs of early career scientists in radiation protection
Bibliographic record
Abstract
Early career researchers, professionals, and scientists (ECRs) are essential to the future of radiation protection, a field that increasingly relies on interdisciplinary collaboration and innovation. In line with the principles outlined in the Vancouver Call for Action for Radiation Protection Researchers, an ICRP (International Commission on Radiological Protection) initiative, this article explores the current landscape for ECRs through the lens of survey data, initiative outcomes, and the establishment of the Early Career in Radiation Protection Network (ECRad). Drawing on a Europe-wide survey of 47 ECRs, the study identifies key areas of concern: while there is strong intrinsic motivation to remain in the field, perceived feasibility is often hampered by job insecurity, fragmented institutional support, and lack of structured mentorship. Although most respondents participate in existing networks such as ICRP, EURADOS, and IRPA, many reported unmet expectations, particularly in mentorship, sustained peer interaction, and accessible professional development. The formation of the RadoNorm Early Career Researcher Council (ECRC) responded directly to these gaps, demonstrating that self-organized, ECR-led initiatives can significantly enhance a sense of belonging and interdisciplinary engagement. However, structural barriers - such as time, funding, and short-term project support - persist, echoing the Vancouver Call for Action's call for improved education, training, and retention. In conclusion, while considerable progress has been made in addressing the needs of ECRs in radiation protection, gaps that threaten the long-term vitality of the field remain. The findings affirm the urgency of coordinated action among institutions, networks, and funding bodies to invest in and empower the next generation of radiation protection professionals.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".