Reassessing the safety of nuclear power. Wheatley

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Volume 15, May 2016, Pages 96–100

Reassessing the safety of nuclear power



We summarize the results of a recent statistical analysis of 216 nuclear energy accidents and incidents (events). The dataset is twice as large as the previous best available. We employ cost in US dollars as a severity measure to facilitate the comparison of different types and sizes of events, a method more complete and consistent that the industry-standard approach. Despite significant reforms following past disasters, we estimate that, with 388 reactors in operation, there is a 50% chance that a Fukushima event (or more costly) occurs every 60–150 years. We also find that the average cost of events per year is around the cost of the construction of a new plant. This dire outlook necessitates post-Fukushima reforms that will truly minimize extreme nuclear power risks. Nuclear power accidents are decreasing in frequency, but increasing in severity.

1. Introduction

It has been more than four years since an earthquake and tsunami caused an accident at the Fukushima Daiichi nuclear power plant in Japan resulting in repeated fires and three reported core meltdowns. At the latest count, the accident had caused $166 billion in damages1[1] and at least 573 immediate deaths from the evacuation, along with hundreds of future deaths related to cancer anticipated to occur [2]. Somewhat sweeping industry reforms were called for, and public acceptance of the technology plummeted [3]. Supporters of nuclear power were quick to point out that a complete phase out would complicate efforts at mitigating greenhouse gas emissions from the electricity sector [4] and could lead to cumulative global losses in global gross domestic product [5].

The March 2011 Fukushima nuclear accident is a poignant reminder that disasters of enormous consequences can occur in the nuclear industry. But how often and with what severity? These two questions constitute the core of sound risk management, which requires identifying and quantifying such potential losses and their frequencies. For most natural and human-made catastrophes such as earthquakes, meteorites, avalanches, mountain collapses, forest fires, hurricanes, epidemics, health care costs, war sizes, terrorist intensities, cyber risks, dam failures, industrial disasters, and so on, plentiful historical data has allowed scientists and engineers to determine the distributions of losses.

The admittedly favorable situation of a paucity of nuclear accidents, combined with scantly available public historical data, has prevented any such statistical analysis. Nuclear engineers have thus resorted to the classification of hypothetical accident scenarios deemed credible and of their potential consequences. The common industry approach to assessing nuclear accident risk depends on a technique known as probabilistic safety analysis (PSA), which assigns probabilities and damage values to particular failure scenarios. Nonetheless, such techniques are known to poorly predict events and to under-appreciate incidents that cascade into failures [6], [7], [8], [9], [10], [11] and [12].

Similarly, the IAEA (International Atomic Energy Agency) provides the INES (International Nuclear Event Scale) to communicate the severity of nuclear accidents on a progressive discrete scale of 1 (anomaly) to 7 (major accident), meant to correspond to the amount of radiation released by order of magnitude. Yet its approach has been critiqued for offering relatively crude scores, for reporting only a fraction of known events, for not being transparent in its methodology, and for being more of a public relations tool (propaganda) than a meaningful metric [9] and [13]. For instance, there are about 12,000 events reported by French operators every year, of which 600–800 are classified annually as “significant for nuclear safety,” yet little to none of these show up on the INES database, and such unreported events occur at just 15% of the currently operating world nuclear fleet [14].

In this study, we summarize the results of a statistical analysis of a dataset of 216 events (incidents and accidents) occurring in nuclear energy systems [15], a dataset that is twice as large as any of the previous best ones available in the scientific literature [8,16], but we refrain from using the INES data directly. Instead, we use the estimated cost in USD (US dollars) as the common metric that allows one to compare often very different types of events across the nuclear fuel cycle. This dataset has more than three times the number of accidents compared with studies using solely the INES data, providing a much better basis for statistical analysis and inference, and a better comparative tool for reassessing the safety of nuclear power. Following Chernobyl, several authors proposed utilizing a monetary value of damage severity to make events comparable, and use a rate measure normalized by the number of reactor operating years to consider frequency [17], [18] and [19]. This is what we have done here, but extending the range of analysis well beyond 1986 to include Fukushima and other nuclear events leading up until the end of 2014. The dataset has been published online2, where the public is encouraged to review and recommend additions and modifications with the intention of continually expanding and improving the quality of the data.
2. Methods

There are many ways to quantify the risk of accidents in nuclear energy systems. The Farmer curve is one of the standard tools of nuclear risk assessment, with the risk defined as “probability × consequences” [20]. Typical Farmer plots display the annual frequency of fatalities or of property damage from human made sources of risk. Remarkably, the nuclear risks reported in Farmer plots are fundamentally different from all previously mentioned risks, in that the distributions for nuclear event losses are always thin-tailed and Gaussian-like, presenting a downward concave shape in the standard log–log representation.

The appearance of the Soviet Union’s Chernobyl accident in 1986 and of Japan’s Fukushima Daiichi nuclear power plant accident, after the tsunami on 11 March, 2011, seem at odds with the statistics implied by the Farmer curves. Actually, following the Chernobyl accident, Hsu [17] and Sengor [18] and [19] suggested a different approach, based on the reasoning that the number of fatalities is an incomplete, if not misleading, metric for measuring nuclear losses given the difficulties in assessing long term real mortality in addition to early morbidity and mortality. Indeed, this metric misses many other dimensions and also prevents quantitative comparisons. Hsu in particular made the point that the statistical analysis of earthquake risks, for instance, would have missed the fundamental Gutenberg–Richter magnitude–frequency law [21] if seismologists had focused on only the few large earthquakes. By considering a range of event sizes above which the data is known to be sufficiently complete, or at least representative, one can identify possible statistical regularities that are relevant to the largest events.

Here, we analyze the distribution of losses resulting from all possible types of nuclear events from 1952 to 2014. To be consistent with both the INES, as well as earlier peer-reviewed studies [8] and [9], we assessed events across the entire nuclear fuel cycle—that is, not only at nuclear reactors and power plants but also at uranium mills, fuel enrichment facilities, reprocessing stations, and nuclear waste repositories. In addition to maintaining consistency, this inclusion of non-reactor events is also necessary to trace the full impact of nuclear power technology on society as well as to account for the fact that many sites prone to accidents concentrate multiple elements of the fuel cycle in one location.3 Searching historical archives, public utility commission filings, regulatory reports, and other sources explained in SM1, we created a unique dataset of 216 nuclear events, with 104 of these events having at least $20 million in inflation-adjusted cost.4 In addition, whenever events had the same dependent cause, such as Fukushima, we treated them as a single occurrence. As it is important to evaluate the number of accidents relative to the number of reactors in operation, we have normalized our assessment to operational reactor data from the IAEA [22].

To be fair, a few caveats and limitations deserve mentioning. In this study, we focus only on damage and loss of life from nuclear accidents, and not other externalities such as lung cancer risks from coal mining or particulate pollution from petroleum-fuelled automobiles. Consequently, our study details the risks present from continuing to operate existing reactors, it does not assess the risks from not operating them (such as greater reliance on fossil fuels) [4]. Also, as is typically the case in data such as this, there is an event severity level below which events are less frequently reported, or even noticed—making our analysis conservative because of incomplete data. We base our analysis on the current reactor fleet, heavily tilted towards older light water reactors (often called “Generation II” technology), not state-of-the-art designs such as the European Pressurized Reactor or “paper” units at the conceptual stage such as small modular reactors, primarily because there is insufficient operating experience for their statistical analysis, but also since the adoption of these designs is uncertain. Our characterization of the current risk level, and its use for forecasting, presumes that 388 reactors remain in operation, and does not include any potential improvements in response to Fukushima. Any significant nuclear renaissance or massive build-out would alter our characterization, as would any massive phase-out. Lastly, we limit our assessment to nuclear generated electricity and its fuel cycle, and thus exclude risks posed by nuclear explosives and nuclear weapons, except for those facilities (such as reprocessing spent fuel) that are dual use.
3. Results and discussion

We quantify four identifiable dimensions of risk: (i) historical frequency of accidents, (ii) historical costs, (iii) the presence of so-called “dragon kings” and extreme events, and (iv) expected future costs.

In terms of frequency, panel (I) of Fig. 1 plots the number of events with at least $20 million in damage (and standard errors) per reactor per year, calculated on 5 year windows spanning 1960 to 2014. The main message here is that the rate of events has dropped substantially since the 1960s, and may have stabilized since the late 1980s. In panel (II) of Fig. 1 the rate of events is calculated running away from the Chernobyl accident in both directions. From here it is clear there was a significant decline in event frequency after the Chernobyl accident, and the rate of events since that drop has been roughly stable, indicating that Chernobyl was a catalyst for change that decreased the rate of events, but not necessarily the size of each event. Rate estimates for 2014 remain in a conservative range of 0.0025–0.0035, or 1–1.4 events per year over the entire nuclear fleet. The methodology used here is described in SM2.

In terms of historical severity, panel (III) of Fig. 1 plots both cost and the Nuclear Accident Magnitude Scale (NAMS) [9] according to a complementary cumulative distribution function (CCDF) described in SM3. As the figure demonstrates, the damage CCDFs corresponding to the periods of before and after the Three Mile Island (TMI) major accident of 1979 are different. It is most plausible that this change was a reaction to TMI, which involved both improving safety standards as well as reporting more events.

We also find that the heavy tailed Pareto distributions are insufficient to account for the extreme empirical tails in the sense that a few exceptional events are “outliers”, or better said, are dragon-kings, revealing the existence of transient amplification mechanisms. Such dragon-kings are found to “coexist with power laws in the distributions of event sizes under a broad range of conditions in a large variety of systems” [23]. As described in SM4, the presence of dragon-kings provides a diagnostic for the existence of causal factors behind accidents not apparent from the main Pareto model used for the distribution. The dragon-kings are shown with X marks in panel (III) of Fig. 1. The main point here is that post-TMI moderate severity events are suppressed but extreme events escalate to the extent that statistically significant dragon-kings emerge in both NAMS and damage, exhibiting a runaway disaster regime.

Next, bringing together models for rates and magnitudes, we quantify the current risk level for the existing nuclear fleet, which may be used as a status-quo characterization of the future risk level using the methods described in SM5. Presuming a low rate λ = 0.002, and without considering the effect of dragon-kings, the 0.99 quantile is $54.3 billion, almost five times the estimated damage from Three Mile Island. Presuming the moderate rate λ = 0.003, with the dragon-king effect, this quantile is $331.6 billion, which is almost double the estimated damage of Fukushima. In other words, there is a 1% probability each year that an accident occurs that leads to a loss of at least $331.6 billion. Such large numbers do not appear to be taken into account in standard calculations on the economics of nuclear power [24]. Moreover, according to our analysis, with 388 reactors in operation, there is a 50% probability of a Fukushima-like event (or more costly) every 60–150 years, and a Three Mile Island event (or more costly) every 10–20 years.

Finally, panel (IV) of Fig. 1 compares our estimated costs with INES scores, indicating inconsistencies where events deviate from the exponential growth in cost qualified by the line in the logarithmic scale. The multitude of dots above or below the INES scale strongly suggest it fails to adequately capture the magnitude of events. For instance, Fukushima (the largest event) would need to have an INES score of 10.6 to be consistent. Further, there is considerable uncertainty in the INES scores as evidenced by the overlapping costs.
4. Six conclusions and policy implications

Our study reveals six important conclusions about the risks of nuclear power. First, concerning event frequency, our analysis shows that the rate of civil nuclear accidents over time since 1952 decreased significantly from the 1970s, reaching what appears to be a stable level of around 0.003 events per plant per year. In this sense, nuclear power is getting safer, although this improvement could be offset by the construction and operation of many new facilities. We find concrete evidence of a history of learning from previous accidents within the industry, especially the significant reduction in event frequency after the Chernobyl accident in 1986, and a suppression of moderately large cost events after TMI.

Second, however, is that these past reforms, rather than minimizing risk, have apparently spawned the prevalence of dragon kings and accidents with major costs. Chernobyl and Fukushima are both such dragon kings, as they together represent 84 percent of the total damage in our dataset. The morphology of nuclear accident risk has altered from more frequent, less costly events to less frequent, more costly events.

Third, existing databases are woefully incomplete when it comes to the reporting of nuclear incidents and accidents. For instance, only half of the events in our database have INES scores, and thousands upon thousands of small events – but with the potential to cascade into larger ones – remain unreported. As the authors of [14] concluded, “many nuclear safety related events occur year after year, all over the world, in all types of nuclear plants and in all reactor designs and that there are very serious events that go either entirely unnoticed by the broader public or remain significantly under-evaluated when it comes to their potential risk.” A fully transparent, centralized source of reliable data on nuclear accidents is needed; one that enables planners, investors, and even nuclear regulators to better comprehend, and then weigh, nuclear risks. Such full disclosure will need to be balanced with the legitimate security concerns of the nuclear industry and the need to avoid promoting a culture of panic and hysteria.

Fourth, apart from being incomplete, industry standard tools such as the INES scale of the IAEA are inadequate and inconsistent at identifying and projecting nuclear accident risk, especially related to dragon kings. For the costs to be consistent with the INES scores, the Fukushima disaster would need to be between an INES level of 10 and 11, rather than the maximum level of 7. To use an analogy, the INES scale is like the antiquated Mercalli scale for earthquake magnitudes, which was replaced by the continuous physically-based Richter scale. Instead of INES, we recommend the use of continuous scales genuinely based on relevant physical variables (radiation emission as in NAMS) and/or economic metrics (dollar costs as proposed here) and that these scales be publicly disclosed for as many events as possible, including all of those in our database.

Fifth, we need to better understand “near misses,” “false negatives,” “minor mishaps,” and “residual risk” [14]. Our study has focused only on “extreme risk,” that is, accidents that precipitated at least $20 million in damages, but an entire class of narrow escapes exist, unplanned or unanticipated events and warnings that never resulted in damage [25] and [26]. In the European Union, for example, legislation called the Seveso directive5 has emphasized, since 1982, the importance of near-misses for hazardous accidents on land, especially in the oil and gas industry. A similar directive ought to be considered for the nuclear industry, and it requires a complete data set of both small and large events to properly quantify the frequency with which small events escalate into larger ones.

Sixth, future frequency and severity of accidents are perhaps unacceptably high. While the nuclear industry can be characterized by an impressive improvement in incident prevention and safety procedures, our thorough analysis of this new data shows that, when a nuclear event of at least $20 million in damage occurs, the probability that it transforms into a catastrophe with damage larger than one billion dollars is almost ten percent. Under the status quo, we project at least one Fukushima-scale dragon king (or larger) accident with 50% probability every 60–150 years. And, more common but still expensive events of about $20 million will occur with a frequency of about one per year—making accidents a relatively routine part of nuclear power’s future.

In conclusion, although the frequency of events per reactor has become less common, the relative frequency with which events cascade into “dragon king” extremes is large enough that, when multiplied by severity, the aggregate risk to society is still very high. To effectively reduce this risk, the possibility of Chernobyl and Fukushima sized events needs to be better anticipated and then more effectively managed.

To solicit as much critical feedback as possible, we posted a working paper using a different methodology and dataset on this topic in April, 2015 available here The working paper does not replicate the data presented in this study, although it does host publicly our dataset so that readers and others can continually improve the robustness and completeness of its contents. We also thank seven anonymous reviewers for extremely helpful comments on earlier versions of this draft, as well as colleagues MV Ramana from Princeton University, Per Peterson from the University of California Berkeley, Mycle Schenider from the World Nuclear Industry Status Report, Mark Cooper and Peter Bradford from Vermont Law School, and Andy Stirling and Gordon MacKerron from the University of Sussex. Despite their input, the findings and conclusions in this study derive only from the authors.

Appendix A. Supplementary data

The following are Supplementary data to this article:


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T.W. van der Schaaf (Ed.), Near Miss Reporting as a Safety Tool, Butterworth-Heinemann (1991)
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One of the authors of this paper is an editor for Energy Research & Social Science. They were not involved in managing the peer review process for this article.

Corresponding author. Fax +45 3032 4303.


Updated to US$2013 and adjusted to monetize human fatalities. Originally reported as $150 billion in $2010 damages.




Sellafield in the United Kingdom, for instance, is home to commercial reactors, research reactors, waste repositories, and reprocessing facilities and Fukushima Daichi in Japan was home to commercial reactors and waste repositories.


The analysis here is focused on events with at least $20 million USD in damage. These events are more visible and thus the dataset is more likely to be complete above this threshold. Therefore statistics on this subset will be more reliable than when considering smaller events. Further, these large events are most relevant as they drive the total risk level. For instance, the ten most costly events contribute approximately 94% of total costs to date.


Copyright © 2015 The Authors. Published by Elsevier Ltd.



NATIONAL ACADEMIES OF SCIENCE, 2016 : Lessons Learned from the Fukushima Nuclear Accident, PHASE 2…..

Source Link:

Fukushima Nuclear Accident
U.S. Nuclear Plants


Committee on Lessons Learned from the Fukushima Nuclear Accident
for Improving Safety and Security of U.S. Nuclear Plants

Nuclear and Radiation Studies Board
Division on Earth and Life Studies

Washington, DC

International Standard Book Number-13: 978-0-309-38888-7
International Standard Book Number-10: 0-309-38888-0
Digital Object Identifier: 10.17226/21874

The following is extracted from the Summary of Findings:


“Spent fuel was stored in eight locations at the Fukushima Daiichi plant on March 11, 2011: in spent fuel pools in each of the six reactor units (Units 1-6), in a common spent fuel pool, and in a dry cask storage facility. The present report focuses on spent fuel storage in the Unit 1-4 pools because these units sustained severe damage as a result of the March 11, 2011, earthquake and tsunami.

The committee finds (Finding 2.1) that the spent fuel storage facilities (pools and dry casks) at the Fukushima Daiichi plant maintained their containment functions during and after the March 11, 2011, earthquake and tsunami. However, the loss of power, spent fuel pool cooling systems, and water level- and temperature-monitoring instrumentation in Units 1-4 and hydrogen explosions in Units 1, 3, and 4 hindered efforts by plant operators to monitor conditions in the pools and restore critical pool-cooling functions. Plant operators had not planned for or been trained to respond to the conditions that existed in the Unit 1-4 spent fuel pools after the earthquake and tsunami. Nevertheless, they successfully improvised ways to monitor and cool the pools using helicopters, fire trucks, water cannons, concrete pump trucks, and ad hoc connections to installed cooling systems. These improvised actions were essential for preventing damage to the stored spent fuel and the consequent release of radioactive materials to the environment. The committee recommends (Recommendation 2.1) that the U.S. nuclear industry and its regulator give additional attention (described in Chapter 2) to improving the ability of plant operators to monitor real-time conditions in spent fuel pools and maintain adequate cooling of stored spent fuel during severe accidents and terrorist attacks.

The spent fuel pool in Unit 4 was of particular concern because it had a high decay-heat load. The committee used a steady-state energy-balance model to provide insights on water levels in the Unit 4 pool during the first 2 months of the accident (i.e., between March 11 and May 12, 2011). This model suggests that water levels in the Unit 4 pool declined to less than 2 m (about 6 ft) above the tops of the spent fuel racks by mid-April 2011. The model also suggests that pool water levels would have dropped below the top of active fuel6 had there not been leakage of water into the pool from the reactor well and dryer/separator pit through the separating gates. This water leakage was accidental; it was also fortuitous because it likely prevented pool water levels from reaching the tops of the fuel racks. The events in the Unit 4 pool show that gate leakage can be an important pathway for water addition or loss from some spent fuel pools and that reactor outage configuration can affect pool storage risks.

The events in Unit 4 pool have important implications for accident response actions. As water levels decrease below about 1 m above the top of the fuel racks, radiation levels on the refueling deck and surrounding areas will increase substantially, limiting personnel access. Moreover, once water levels reach approximately 50 percent of the fuel assembly height, the tops of the rods will begin to degrade, changing the fuel geometry and increasing the potential for large radioactive material releases into the environment.
end quote. emphasis added.

Other than that, there was absolutely nothing to worry about and anyone who disagrees is a radiophobe. For the nuclear industry and nuclear authorities have always known precisely what it has been doing and no one is able, in its view, to question those authorities rationally. They say.

Key words and terms:

Comparison with press and other technical records of the state of SFP 4:
Pivotal events occurred on 14, 15 March 2011 and the Japanese government, the IAEA and disaster response measure changes on those days all confirm that these pivotal events did indeed occur. These events are recorded by the following official, qualified and press sources:

Questions to be put to Mr Shepherd, author, Caltech:

Is the SA Government Sufficiently Open & Transparent to run a Global High Level Nuclear Waste Dump?

The State Government of South Australia maintains that it is a good idea for this state to become the site of a global High Level Nuclear Waste Dump.  It plans to store a large proportion of the world’s spent nuclear reactor fuel rods deep underground on Eyre Peninsular. Part of this Peninsular is a food bowl for the state, the nation and the world.

The South Australian government plans to receive the high level nuclear waste via a purpose built port in South Australia and via the port of Darwin.  The waste will be trucked across Australia for firstly, above ground holding, and then permanent geologic storage inside cooper tubes designed in Scandinavia.

The state government has issued a Royal Commission into SA’s role in the nuclear future.  Chapter 7 of the report concentrates upon the safety of nuclear industry.  Chapter 7 makes many statements about the comparative contribution various sources, natural and man made, make to a public annual radiation dose.

All of the statements contained in Chapter 7 of the report rely upon monitoring of radiation in the environment from all sources, and it relies upon estimates of the doses received by member of the public.  Unlike radiation workers in any field, for example in mining or medicine, the members of the public are not monitored for their individual personal doses on a day by day basis. And so the annual dose for members of the public is a an average, a best guess.

Where governmental radiation protection regimes are trusted by the people of a nation, and where government is trusted by those people to release information in an open and honest manner, and where that information is released in full and in a timely manner, then such a people, such a society enjoys the trust of government. And the people tend to accept the facts as presented by government.   The job of government is to be open and honest.  The job of the people is to guard against deception, delay and falsehood.

Radiation monitoring is a primary duty of government. For example South Australian water supplies have been monitored in this way for many decades.  Generally, few people are interested in the monitoring results.  This is true of any monitoring, whether it be for smog in the air, bacteria in the water supply, and the safety of food.  We tend to trust that government authorities will inform the public in an open, honest, and timely fashion.

The government of South Australia has advised the people of this state that the decision to proceed or not to proceed with the development of a global graveyard for the world’s waste reactor cores is too important to be left to the mere democratic processes we all know, love and suffer loss in war for.  That is, the government has determined that we are not allowed a free and secret ballot on the question.  The Premier of the State has advised us that he will make the decision in due course.

After a relentless campaign since 2011 to convince us, via decrees from Flinders and Adelaide University, that the Linear No Threshold Model of radiological protection is invalid – though there is at least insufficient evidence to support Hormesis as a cheap alternative (much to the chagrin of the uranium lobby), the power elite in this State is now denying us the right and freedom to vote on the matter.  There is to be a long term propaganda process whereby local “community juries” – small groups of individuals drawn from the community by the government – will be inculcated into the consensus the government and industry require.

I have a major problem with the SA government plan for a high level nuclear waste dump located in this state.














Dedicated to the Dude at Fukushima Syndrome

We live in a cusp between technologies. The esoteric today is tomorrow’s conventional.

No amount of optimistic revisionism will successfully hide the short comings of technologies held by people to be inconsequential when such people are in fact the Luddites of both today and tomorrow.

Why boil water with 26 different types of university degrees, a process which generates nuclear waste no user nation really wants to store. The world is seriously considering exported to my home, South Australia, for storage for the next 100,000 years ? This is madness. There are no NPPs in Australia.

The proposed HLNW dump is smack bang to the immediate north of one of South Australia’s food bowls.

The whole globe really expects us to mind its nuclear sewerage for the next 100,000 years? How stupid do you think we are?

In all sincerity I say to the proponents of this mad plan – please Fuck off, Yankee go home.

Is that clear or shall I repeat it?

The School of Hormesis and its terms of abuse, stigmatisation, and political and social isolation

Published by Flinders University in the public domain.

Notice to Flinders University:

May 26th, 2016 at 1:59 pm

I am now at the point where I am fully prepared and able to present a complaint to both State and Federal human rights and EEO authorities about the impacts of the 2011 Sykes article here. The basic infringements being the exclusion of people deemed to be, judged to be or actually suffering mental health issues, whether radiophobia or any condition is actually (unlike radiophobia,an invention of the school of Hormesis. It does not appear in any relevant diagnostic manual such as DSMIV), with a primary breach to the rights of dissidents who disagree with the concepts of hormesis as a means of social control (as evidenced by the Sykes piece) or as a method by which alleged safety can be imposed upon populations.

In combination, in fact and in theory the stance of hormesis as published by Scott (LANL, USA) and Sykes and FU primarily breaches the rights of dissidents to fully participate in the current and ongoing nuclear debate as determined and invited by the current government of SA. To participate results in advocates of ALARA being labelled as mentally defective by Sykes and Flinders University. This breaches many human rights, including relevant sections of the Universal Declaration of Human Rights, including, but limited to, the following:

Article 2.

Everyone is entitled to all the rights and freedoms set forth in this Declaration, without distinction of any kind, such as race, colour, sex, language, religion, political or other opinion, national or social origin, property, birth or other status. Furthermore, no distinction shall be made on the basis of the political, jurisdictional or international status of the country or territory to which a person belongs, whether it be independent, trust, non-self-governing or under any other limitation of sovereignty.
Article 3.

Everyone has the right to life, liberty and security of person.

Article 12.

No one shall be subjected to arbitrary interference with his privacy, family, home or correspondence, nor to attacks upon his honour and reputation. Everyone has the right to the protection of the law against such interference or attacks.

Article 19.

Everyone has the right to freedom of opinion and expression; this right includes freedom to hold opinions without interference and to seek, receive and impart information and ideas through any media and regardless of frontiers.

Article 27.

(1) Everyone has the right freely to participate in the cultural life of the community, to enjoy the arts and to share in scientific advancement and its benefits.
(2) Everyone has the right to the protection of the moral and material interests resulting from any scientific, literary or artistic production of which he is the author.
Article 28.

Everyone is entitled to a social and international order in which the rights and freedoms set forth in this Declaration can be fully realized.

(1) Everyone has duties to the community in which alone the free and full development of his personality is possible.
(2) In the exercise of his rights and freedoms, everyone shall be subject only to such limitations as are determined by law solely for the purpose of securing due recognition and respect for the rights and freedoms of others and of meeting the just requirements of morality, public order and the general welfare in a democratic society.
(3) These rights and freedoms may in no case be exercised contrary to the purposes and principles of the United Nations.

I observe that the aim of Hormesis and of US DoE Contractors appointed in Adelaide is to socially isolate those South Australians who disagree with hormesis and who hold contrary knowledge and opinions to that school of thought. As an advocate for ALARA, the school of Hormesis has mainted that people with allegedly deviant views are incapable of rational thought, are ignorant and are unreasonably fearfull of the edicts issued by the school of hormesis. I maintain that since 2011 at least, the school of hormesis in SA has profiled objectors to its position as mentally defective, and has carefully tried to induce the wider community to exclude such dissidents from full social inclusion and participation. This is particularly injurious given the current standing invitation for all South Australians to fully participate in the current nuclear debate which has been in fact on going since 2011. I ask again, Flinders University must stop its attempts to isolate dissidents to the school of hormesis or fact investigation by state and federal and international bodies.

Paul Langley

anyone else like to be included in this complaint?
Fukushima Syndrome perhaps? When is Bobby Scott’s and Lanl legal notice advising me I am to be sued due to my dissent going to arrive you Moron?