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Ethical Considerations Concerning the Regulation of Human Exposure to Electromagnetic Fields

2000· article· en· W2313655357 on OpenAlexaff
Caterina Botti, Pietro Comba

Bibliographic record

VenueEpidemiology · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicRisk Perception and Management
Canadian institutionsBC Studies
Fundersnot available
KeywordsEngineering ethicsMedicineEngineering

Abstract

fetched live from OpenAlex

Various opinions exist with respect to what should be the role of epidemiologists in the definition of public health policy and what should be the code of conduct in setting policy in the face of uncertainty. 1–8 The issue we wish to discuss is the situation in which the number of attributable cases tends to be small and health benefits must be balanced against relatively high costs of prevention. We use as an example the debate over human exposure to electromagnetic fields. Following the pioneering study by Wertheimer and Leeper, 9 several authors have pursued this topic in different countries. Recently, the National Institute of Environmental Health Sciences in the United States has classified magnetic fields as possible carcinogens, according to the criteria of the International Agency for Research on Cancer. 10 This classification means that the number of attributable cases might in principle even be zero, although, notwithstanding the limitations of study design and the lack of a plausible biological mechanism - the association is regarded as “credible.” In that light it is reasonable to evaluate the merits of various preventive measures. The etiological fraction was estimated to be “small” by Olsen et al11 in Denmark. In Finland, exposure to magnetic fields of transmission power lines at levels close to 0.2 μT did not pose “a major public health risk” according to Verkasalo et al, 12 whereas Valjus stated that “even an extra childhood cancer would be ethically too many”. 13 In Germany Michaelis et al estimated that eight cases of childhood leukemia per year could be attributed to exposure to magnetic fields of 0.2 μT or more. 14 They concluded that despite the tragic fate of affected families, the excess risk associated with exposure to electromagnetic fields has to be evaluated in comparative terms with respect to other excess risks concerning children. In 1996, the Swedish National Boards of Occupational Safety and Health, Housing Building and Planning, Electricity Safety, Health and Welfare and the Radiation Protection Institute issued a document offering “guidance for decision-makers” on this issue. 15 It is claimed that although research findings provide no basis for and cannot justify any safety limits or other restrictions on low-frequency electrical and magnetic fields, a “certain amount of caution” may be justified where this kind of exposure is concerned. 15 The document claimed that although “a human life cannot be valued in money,”15 finite resources makes it impossible for society to save all lives or avert serious illness, thus some balancing is necessary. In all these claims one sees emerging the core issue of deciding whether it is acceptable to leave a small fraction of population to face an increase of risk when the cost of mitigation is expensive for society. Even if a final decision on risk management is taken at the societal level, the input from epidemiologists is relevant to the process. This relevance is underscored when an epidemiologic study estimates a small number of attributable cases in the absence of any comment on the distribution of such cases in various population subgroups. In other words, epidemiologists may not necessarily take a stand in the public health debate, but their findings are heavy with implications nonetheless. Awareness of these implications may be crucial to fulfilling one’s professional obligation as an epidemiologist, according to Weed and McKeown, 8 and it may facilitate practical solutions to policy problems. For electromagnetic fields, the increase in morbidity and mortality affects a small fraction of the population, whereas the cost for the community to avoid this increase is large. Similar conflicts in public health have traditionally been managed on the basis of a cost benefit analysis aimed at maximizing collective welfare. The implicit assumption is that it is not possible to eliminate risks completely, but that they must be minimized where possible. According to this approach there can be situations in which it is not considered immoral for a limited fraction of the population to be exposed to a risk factor that is expensive for the community to remove. Nonetheless, this attitude contrasts not only with the traditional approach of clinical medicine, but also with the preventive aim of epidemiology and public health, 16 according to which the life of each individual has unlimited value. It is widely held that the core values of epidemiology are defined by two different and sometimes conflicting models, the model of public health supporting the public good, and the model of medicine supporting the good of the individual. 17,18 In this second model, the attribution of “an absolute value to a person” is a “fundamental axiom, indispensable for defining the concepts of health and disease that would otherwise escape any definition made purely on objective grounds.”19 These two approaches, with different “core values,” underlie the practice of both environmental epidemiology in particular and epidemiology more generally. 20–22 Usually they can blend together, but sometimes, as for electromagnetic fields, conflict may develop. The two approaches can be cast in terms of “commensurability”vs “incommensurability,” adopting the concepts used in the broad philosophical debate concerning “tragic choices.”23,24 Commensurabilists think that because we cannot avoid tragic choices, we should attach measurable values to the alternatives and try to maximize the general welfare by balancing the alternatives through cost-benefit analysis. Incommensurabilists believe that it is sometimes inappropriate to make comparisons (for instance when human life is at stake), or that while choosing among alternatives it is not always necessary to judge their comparative value. 23 With respect to electromagnetic fields, the question is—must we assign a calculable value to human life and consider a few children to be a negligible cost, or is there another way to make a decision? The question reminds us of the Swedish document that states that “a human life cannot be valued in money” and that the possibilities for societies are limited by the lack of resources. The last section of the document deals with preventive action. Both the number of exposed subjects and the cost of the intervention are taken into account. The cost for estimated prevented case can be a criterion in the evaluation of the feasibility of interventions and in setting priorities. This procedure, although based on a calculation, can be read paradoxically as a sort of incommensurabilist effort: the effort to deal with the problem of a few children, to take into account the value of life (and not to value it) as far as resources (and scientific evidence) allow. In this case the “visibility” of a few children can lead to interesting solutions that are not utopian, and do not deny the importance of the lives of those few children. For example, one solution might be to concentrate preventive efforts in places dedicated to children, such as schools and kindergartens. This solution can be viewed as an application of the precautionary principle, a claim that resonates with Weed and McKeown’s recent call for prudence 8 in linking public health science with public health action, even in the face of uncertainty. We believe that, although they conflict, both commensurabilist and incommensurabilist approaches are at the core of the epidemiologic profession. Solutions must be sought case by case. Being aware of this conflict is a moral imperative for epidemiologists. Awareness seeds the search for a just solution or compromise and enhances communication between scientist, regulators, and the general public. Rendering explicit the moral values underlying the various positions held by public health scientists may in fact represent the first step in improving mutual understanding of, to some extent, apparently conflicting opinions. Acknowledgments We thank Terri Ballard, Roberta Pirastu, and Paolo Vecchia for helpful comments and criticism.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.634
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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)0.0100.000

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 head0.104
GPT teacher head0.404
Teacher spread0.300 · 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.

Study designTheoretical or conceptual
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".

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Citations3
Published2000
Admission routes1
Has abstractyes

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