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Record W4390203051 · doi:10.1177/01466453231177505

(Un)stated assumptions: values, ethics, and the System of Radiological Protection

2023· article· en· W4390203051 on OpenAlexaffabout
R. Velshi

Bibliographic record

VenueAnnals of the ICRP · 2023
Typearticle
Languageen
FieldEngineering
TopicNuclear and radioactivity studies
Canadian institutionsCanadian Nuclear Safety Commission
Fundersnot available
KeywordsMisinformationCLARITYDisinformationUnderpinningCommissionCredibilityPublic relationsEngineering ethicsDeliberationPolitical scienceBusinessLawEngineering

Abstract

fetched live from OpenAlex

The issues of what is ‘safe’ and what is an ‘unreasonable risk’ pre-occupy regulators each and every day. Western science alone is inadequate as a guide. Good advice and good decision-making require consideration of Western science in tandem with traditional knowledge, our personal and organisational ethics and values, and our shared experiences. As the global information environment grows increasingly complex, it is more crucial than ever that international organisations, such as ICRP, and national regulators, such as the Canadian Nuclear Safety Commission, are clear about their ethical guideposts and their core values. Clarity in these anchors allows policy makers and regulators to communicate the rationale for decisions more clearly, and to combat disinformation and misinformation more effectively – a challenge that demands action from us all. As we look towards revising the System of Radiological Protection and implementing it in international and national regulatory systems around the world, codifying and communicating our underpinning assumptions will clearly enhance our credibility and trust, and will enable more effective combination of the guidance offered by the System of Radiological Protection with relevant national considerations, including factors such as societal risk tolerance and indigenous knowledge.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.546
Threshold uncertainty score0.114

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.086
GPT teacher head0.288
Teacher spread0.202 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueAnnals of the ICRPSame topicNuclear and radioactivity studiesFrench-language works237,207