The Campaign to Mislead the Public on Climate Change

Wyoming just became the first state in the nation to reject world-class science standards that teach our kids about climate change. Interest groups that pushed for this move would like to bar climate science from being taught in other states too.

Wyoming legislators voted to support a last-minute budget amendment that prohibits the Wyoming State Board of Education from spending funds to even consider the Next Generation Science Standards (NGSS) because students would learn about climate change in this fossil fuel-dependent state.

Wyoming State Rep. Matt Teeters, who authored the anti-science budget amendment, told the Casper Star-Tribune that teaching climate change as fact would "wreck Wyoming's economy...and cause other unwanted political ramifications." Governor Mead signed the anti-science provision into law.

The Board of Education could push back against political meddling and assert its authority over setting science standards, but it will take an outcry from parents and science supporters from Wyoming and throughout the country.

It is a dangerous precedent to allow those who deny climate science for ideological or economic reasons to censor the science education kids need to be ready for college, career and a changing climate. Science education standards should be written by scientists and educators, not by legislators whose concerns may be more political than educational.

Ten states have adopted the NGSS, a set of science standards for K-12 students developed by an arm of the National Academy of Sciences.But Wyoming could be the beginning of an assault on climate education in the states still considering these 21st century science standards. 

Wyoming students deserve access to high quality, world-class science standards just as much as students anywhere else in the nation. Given the stakes for our children’s future, it’s imperative that kids everywhere learn the facts of climate change so they can all become part of the solution.

Thank you for taking action for our kids and grandkids!

Sincerely,

Marguerite Herman, Advocate for Science Education, Climate Parents Member

Cheyenne, Wyoming

Texas Science Textbook Review

The right-wing majority on the Texas State Board of Education wants to revise the state's standards for science textbooks to require the addition of religious pseudoscience when teaching subjects like biology. And this isn't just bad news for Texas schoolchildren, because the Texas standards will impact the textbooks used by millions of students nationwide.
The Texas State Board of Education recently invited a small group of people to review the biology textbooks that will be used for the next eight years, starting in 2014. But more than half of the reviewers are right-wing religious ideologues,¹ some of whom are even skeptics of Darwin's theory of evolution — considered one of the most reliably established facts in science, and a central tenet of biology.²
The ultimate goal of these sham textbook reviews — and Texas Board of Education curriculum reform — is to enshrine right-wing ideology into Texas textbooks. What's worse, because of the scale of production of these textbooks, the dictates of the Texas State Board of Education will be included in textbooks used by millions of students in other states.
We can't let them get away with replacing long-accepted scientific principles with religious pseudoscience and propaganda.³
Tell textbook publishers to stand up to the Texas State Board of Education and only publish books that are based on sound, peer-reviewed science scholarship. Click here to sign the petition automatically.
The most recent review of biology textbooks was a particularly egregious process considering the people who were invited to participate. Here are just a few of the reviewers who are listed in the Creation Science Hall of Fame as “Darwin Skeptics”⁴:

• Raymond Bohlin, a research fellow for an organization whose purpose is the promotion of “intelligent design” — a religious idea which seeks to cast doubt on evolution while circumventing the Supreme Court ruling that bars the teaching of “creation science” in public schools.⁵
• Walter Bradley, who helped launch the "intelligent design” movement with a book he coauthored, titled The Mystery of Life's Origin.
• Ide Trotter, a wealthy funder of anti-science organizations who has repeatedly participated in science textbook reviews advocating for the inclusion of scientifically discredited theories about the weaknesses of evolution.

Tell textbook publishers to stand up to the Texas State Board of Education and only publish books that are based on sound, peer-reviewed science scholarship. Click here to sign the petition automatically.
Textbook publishers can refuse to make suggested changes, or pull out of the state's business altogether, just as publisher Holt, Rinehart and Winston did in 1994, when Texas requested over 400 revisions in five health textbooks — including the removal of toll-free phone numbers for teenage suicide prevention groups.⁶
We're not going to change the minds of some of the theocrats elected to the Texas State Board of Education. But we can pressure publishers not to compromise their science textbooks by caving to the board's unreasonable demands.
The final review of these textbooks won't happen until November, and these textbooks could be in classrooms for a decade. Now's the time to put pressure on textbook publishers to stop accepting this scientifically debunked information.
Tell textbook publishers to stand up to the Texas State Board of Education and only publish books that are based on sound, peer-reviewed science scholarship. Click the link below to sign the petition automatically:
http://act.credoaction.com/go/1587?t=8&akid=8727.5084505.bx5l8X
Thank you for standing up for science.
Jordan Krueger, Campaign Manager
CREDO Action from Working Assets

Automatically add your name:

Learn more about this campaign

1. Dan, "Alarm Bells Are Ringing: Creationists Get Influential Positions in Texas Science Textbook Review." Texas Freedom Network, July 30, 2013.
2. National Research Council. "Science, Evolution, and Creationism." Washington, DC: The National Academies Press, 2008.
3. Gail Collins, "How Texas Inflicts Bad Textbooks on Us." The New York Review of Books, June 21, 2012.
4. Jenny Bergman, "Darwin Skeptics." Creation Science Hall of Fame.
5. [PDF] Barbara Forrest, "Understanding the Intelligent Design Creationist Movement: Its True Nature and Goals." The Center for Inquiry, May, 2007.
6. Gail Collins, "How Texas Inflicts Bad Textbooks on Us." The New York Review of Books, June 21, 2012.

Refusing to cooperate with Iranian military

Michele Catanzaro

26 April 2013

Omid Kokabee, a former graduate student in physics who has been imprisoned in Iran since January 2011, has written in an open letter that he was being persecuted for refusing to cooperate with Iranian military projects. In another, private letter, he says these projects are related to nuclear applications.

“Is it a sin that I don’t want, under any circumstances, to get involved in security and military activities?” he asks. “I have just turned 30 years old after spending two years in prison, when I am eager to pursue scientific research,” he remarks. Nature received copies of the letters from Kokabee’s contacts, who asked to remain anonymous because of fear of retribution.

In the public letter (read Nature's English translation of the Kokabee letter from the original Farsi), addressed to Ali Sharifi, who Kokabee describes as his former roommate at Sharif University of Technology in Tehran, Kokabee says that he was asked to collaborate with the military before and during his detention, but always refused. 

Neo Middle Ages

Despite the many changes that have taken place in American society and culture over the past 30 years, including new discoveries in biological and social science, there has been virtually no sustained change in Americans' views of the origin of the human species since 1982. The 46% of Americans who today believe that God created humans in their present form within the last 10,000 years is little changed from the 44% who believed this 30 years ago, when Gallup first asked the question.

More broadly, some 78% of Americans today believe that God had a hand in the development of humans in some way, just slightly less than the percentage who felt this way 30 years ago.

All in all, there is no evidence in this trend of a substantial movement toward a secular viewpoint on human origins.

Most Americans are not scientists, of course, and cannot be expected to understand all of the latest evidence and competing viewpoints on the development of the human species. Still, it would be hard to dispute that most scientists who study humans agree that the species evolved over millions of years, and that relatively few scientists believe that humans began in their current form only 10,000 years ago without the benefit of evolution. Thus, almost half of Americans today hold a belief, at least as measured by this question wording, that is at odds with the preponderance of the scientific literature.



Miss USA 2011, the 60th anniversary of the Miss USA pageant.

The Middle Ages (adjectival forms: medieval, mediaeval, and mediæval) is the period of European history encompassing the 5th to the 15th centuries; and normally is marked from the collapse of the Western Roman Empire (the end of Classical Antiquity) until the beginning of the Renaissance and the Age of Discovery, the periods which ushered in the Modern Era. The mediaeval period thus is the mid-time of the traditional division of Western history into Classical, Medieval, and Modern periods; moreover, the Middle Ages usually is divided into the Early Middle Ages, the High Middle Ages, and the Late Middle Ages.

In the Early Middle Ages, depopulation, deurbanization, and barbarian invasions, begun in Late Antiquity, continued apace. The barbarian invaders formed new kingdoms in the remains of the Western Roman Empire. In the 7th century North Africa and the Middle East, once part of the Eastern Roman Empire, became an Islamic Empire after conquest by Muhammad's successors. Although there were substantial changes in society and political structures, the break with Antiquity was not complete, because most of the new kingdoms incorporated many of the extant Roman institutions; while monasteries were founded as Christianity expanded in western Europe. In the 7th and 8th centuries, the Franks, under the Carolingian dynasty, established an empire covering much of western Europe; the Carolingian Empire endured until the 9th century, when it succumbed to the pressures of invasion — the Vikings from the north; the Magyars from the east, and the Saracens from the south.

During the High Middle Ages, which began after AD 1000, the population of Europe increased greatly as technological and agricultural innovations allowed trade to flourish and crop yields to increase. Manorialism — the organization of peasants into villages that owed rent and labor services to the nobles; and feudalism — the political structure whereby knights and lower-status nobles owed military service to their overlords, in return for the right to rent from lands and manors - were two of the ways society was organized in the High Middle Ages. Kingdoms became more centralized after the breakup of the Carolingian Empire. The Crusades, first preached in 1095, were military attempts, by western European Christians, to regain control of the Middle Eastern Holy Land from the Muslims, and succeeded long enough to establish Christian states in the Near East. Intellectual life was marked by scholasticism and the founding of universities; and the building of Gothic cathedrals, which was one of the outstanding artistic achievements of the High Middle Ages.

The Late Middle Ages were marked by difficulties and calamities, such as famine, plague, and war, which much diminished the population of western Europe; in the four years between 1347 and 1350, the Black Death killed approximately a third of the European population. Controversy, heresy, and schism within the Church paralleled the warfare between states, the civil war, and peasant revolts occurring in the kingdoms. Cultural and technological developments transformed European society, concluding the Late Middle Age and beginning the Early Modern period.

---

Dark Ages Redux: American Politics and the End of the Enlightenment

by John Atcheson

 

We are witnessing an epochal shift in our socio-political world.  We are de-evolving, hurtling headlong into a past that was defined by serfs and lords; by necromancy and superstition; by policies based on fiat, not facts.

Much of what has made the modern world in general, and the United States in particular, a free and prosperous society comes directly from insights that arose during the Enlightenment.

Too bad we’re chucking it all out and returning to the Dark Ages. Literally.

The Eternal Return of the Elite

Vilfredo Pareto

http://it.wikipedia.org/wiki/Vilfredo_Pareto



This monograph first saw the light of day in 1901 and has been understood as a somewhat famous attempt at a non race-based understanding of 'elitism'. The failure of this attempt to be either genuinely explanatory or entirely successful seems, by almost all accounts, to have been historically verified by fascisms repeated descent into racism. But, given the utter failure of the Fascist movements of the post World War II era to gain traction, one wonders if perhaps now Pareto can, at last, be given a fair hearing. One even wonders if Pareto is fairly characterized as a fascist.



Be that as it may, Pareto still might have much to teach us about the interactions of elites. According to Pareto, elites rise to power, maintain dominance, and then fall; but only if another elite is struggling to take its place. (One is here reminded of Lenin's remark against Trotsky, I believe, 'that no state ever fell without being pushed'.) History is, according to this text, a circulation of elites; and for Pareto, the ideologies that these elites represent are only of secondary importance. What one must always keep in mind while reading this book is that, for Pareto, Liberals and Socialists (that is, the leaders of these ideological positions) are equally elites. By the 'elite', I should point out, Pareto always means the leadership of a class.



Pareto distinguishes between subjective and objective factors; the latter being real objects while the former are psychological states. Thus belief and unbelief are, for Pareto, equally psychological states. In fact, according to our author, belief is often the sign of a rising elite. Note that by 'belief' he doesn't merely mean religious beliefs; according to Pareto socialism is a belief, that is, it is a psychological state. Indeed, for Pareto, perhaps somewhat surprisingly given his right-wing tendency and reputation, nationalism itself is also a belief. Now, he doesn't propose to ignore these beliefs; on the contrary, it is the skepticism of the rulers towards beliefs that weakens them in the face of the rising elite. These 'myths' are a part of history and need to be explained.



The 'religious sentiment' (i.e., belief) of the masses is what leads to revolt. This sentiment is exploited by the rising elite in its attempt to overthrow the ruling elite. (In this matter the 'skepticism' of the ruling elite is no small aid to the rising elite.) And what we also need to keep in mind is that logical argument almost always fails in these matters; people believe for non-rational reasons, sentiment must be met with sentiment, i.e. socialism must be countered with nationalism. In fact, in these pages Pareto, over a hundred years ago, by describing the similarity between Christian and Socialist behavior, seems to indicate the possibility of a convergence of Christianity and Socialism vis-à-vis the ruling bourgeois. This possibility is currently being explored, thanks to the collapse of 'really existing socialism' in the USSR, by the most au courant leftist continental theory.



Keep in mind that, for Pareto, it is the 'decadence' (i.e., it is 'less apt to defend its own power') and the unabated rapacity of the old elite that causes it to perish. Indeed, he says of this decadence and rapacity that the old elite "could prosper if one of them were absent." Scientifically, or so Pareto maintains, there really is nothing to choose between. Speaking of some historical examples of some crimes of new elites Pareto says, "The old elite, when it was in power, did even worse, so that one cannot conclude from these facts anything against one or the other regime..." Pareto simultaneously holds that reform is the most dangerous moment for the ruling elite, and that the waning of power is perfectly compatible with a rise in the use of violence. In fact, one comes away from this book feeling that the things that Pareto held in most contempt were inefficiency and incompetence and, indeed, some of his most contemptuous gestures in this matter are reserved for the capitalists.



In any case, the problem seems to be that the falling class, no longer believing in itself, can no longer attract the best young people to its cause. The rising class has 'belief' and hope, the falling one only has its privileges. Persecution seems to be no remedy for this. Indeed, thanks to persecutions, "many people of doubtful loyalty and unsteady character were eliminated and professional politicians kept away." ...Very amusing! But here, in 1901, Pareto sees the best of future generations going to socialism while all persecution does is prune the revolutionary plant.



In fact, if one carries away anything from this book it is that old elites must eventually fall. We learn here that socialism is the heir of Christian 'belief'. And since Christianity is dying, all the old elite can do is delay the inevitable 'homecoming' of the common people (and their 'religious sentiment') to socialism. Thus 'belief' replaces 'belief'. Again, there is little rationality in this process; Pareto is at pains to emphasize the 'subjective phenomenon'. This is why nationalism is the best answer to socialism; one counters one irrationality with another.



This book is really only a long essay, the hardcover edition before me has 75 pages of text, 18 pages of notes, and a 22 page introduction. The notes are quite good and should not be passed up. For example, while nicely playing off his understanding of socialism as but another belief, Pareto, after discussing some socialist 'sectarians', writes, "One day we will perhaps have the Holy Inquisition of the socialist faith. (Note 18)" The Soviet 'show trials' of the thirties were indeed this Inquisition. This really is a superb book, a worthy companion piece to all the great political realists of history - from Machiavelli to Gramsci.

there are no facts, only interpretations

Statistics is the study of the collection, organization, analysis, and interpretation of data.^[1][2] It deals with all aspects of this, including the planning of data collection in terms of the design of surveys and experiments.^[1]
A statistician is someone who is particularly well versed in the ways of thinking necessary for the successful application of statistical analysis. Such people have often gained this experience through working in any of a wide number of fields. There is also a discipline called mathematical statistics that studies statistics mathematically.

The word statistics, when referring to the scientific discipline, is singular, as in "Statistics is an art."^[3] This should not be confused with the word statistic, referring to a quantity (such as mean or median) calculated from a set of data,^[4] whose plural is statistics ("this statistic seems wrong" or "these statistics are misleading").

There is a general perception that statistical knowledge is all-too-frequently intentionally misused by finding ways to interpret only the data that are favorable to the presenter.^[14] The famous saying, "There are three kinds of lies: lies, damned lies, and statistics".^[15] which was popularized in the USA by Mark Twain and incorrectly attributed by him to Disraeli (1804–1881), has come to represent the general mistrust [and misunderstanding] of statistical science. Harvard President Lawrence Lowell wrote in 1909 that statistics, "...like veal pies, are good if you know the person that made them, and are sure of the ingredients."^{[citation needed]}

If various studies appear to contradict one another, then the public may come to distrust such studies. For example, one study may suggest that a given diet or activity raises blood pressure, while another may suggest that it lowers blood pressure. The discrepancy can arise from subtle variations in experimental design, such as differences in the patient groups or research protocols, which are not easily understood by the non-expert. (Media reports usually omit this vital contextual information entirely, because of its complexity.)

By choosing (or rejecting, or modifying) a certain sample, results can be manipulated. Such manipulations need not be malicious or devious; they can arise from unintentional biases of the researcher. The graphs used to summarize data can also be misleading.

Deeper criticisms come from the fact that the hypothesis testing approach, widely used and in many cases required by law or regulation, forces one hypothesis (the null hypothesis) to be "favored," and can also seem to exaggerate the importance of minor differences in large studies. A difference that is highly statistically significant can still be of no practical significance. (See criticism of hypothesis testing and controversy over the null hypothesis.)

One response is by giving a greater emphasis on the p-value than simply reporting whether a hypothesis is rejected at the given level of significance. The p-value, however, does not indicate the size of the effect. Another increasingly common approach is to report confidence intervals. Although these are produced from the same calculations as those of hypothesis tests or p-values, they describe both the size of the effect and the uncertainty surrounding it.

In statistics, survey methodology is the field that studies the sampling of individuals from a population with a view towards making statistical inferences about the population using the sample. Polls about public opinion, such as political beliefs, are reported in the news media in democracies. Other types of survey are used for scientific purposes. Surveys provide important information for all kinds of research fields, e.g., marketing research, psychology, health professionals and sociology.^[1] A survey may focus on different topics such as preferences (e.g., for a presidential candidate), behavior (smoking and drinking behavior), or factual information (e.g., income), depending on its purpose. Since survey research is always based on a sample of the population, the success of the research is dependent on the representativeness of the population of concern (see also sampling (statistics) and survey sampling).

Survey methodology seeks to identify principles about the design, collection, processing, and analysis of surveys in connection to the cost and quality of survey estimates. It focuses on improving quality within cost constraints, or alternatively, reducing costs for a fixed level of quality. Survey methodology is both a scientific field and a profession. Part of the task of a survey methodologist is making a large set of decisions about thousands of individual features of a survey in order to improve it.^[2]
The most important methodological challenges of a survey methodologist include making decisions on how to:^[2]

• Identify and select potential sample members.
• Contact sampled individuals and collect data from those who are hard to reach (or reluctant to respond).
• Evaluate and test questions.
• Select the mode for posing questions and collecting responses.
• Train and supervise interviewers (if they are involved).
• Check data files for accuracy and internal consistency.
• Adjust survey estimates to correct for identified errors.

A misuse of statistics occurs when a statistical argument asserts a falsehood. In some cases, the misuse may be accidental. In others, it is purposeful and for the gain of the perpetrator. When the statistical reason involved is false or misapplied, this constitutes a statistical fallacy.
The false statistics trap can be quite damaging to the quest for knowledge. For example, in medical science, correcting a falsehood may take decades and cost lives.
Misuses can be easy to fall into. Professional scientists, even mathematicians and professional statisticians, can be fooled by even some simple methods, even if they are careful to check everything. Scientists have been known to fool themselves with statistics due to lack of knowledge of probability theory and lack of standardization of their tests.

Discarding unfavorable data

All a company has to do to promote a neutral (useless) product is to find or conduct, for example, 40 studies with a confidence level of 95%. If the product is really useless, this would on average produce one study showing the product was beneficial, one study showing it was harmful and thirty-eight inconclusive studies (38 is 95% of 40). This tactic becomes more effective the more studies there are available. Organizations that do not publish every study they carry out, such as tobacco companies denying a link between smoking and cancer, anti-smoking advocacy groups and media outlets trying to prove a link between smoking and various ailments, or miracle pill vendors, are likely to use this tactic.

Another common technique is to perform a study that tests a large number of dependent (response) variables at the same time. For example, a study testing the effect of a medical treatment might use as dependent variables the probability of survival, the average number of days spent in the hospital, the patient's self-reported level of pain, etc. This also increases the likelihood that at least one of the variables will by chance show a correlation with the independent (explanatory) variable.

Loaded questions

The answers to surveys can often be manipulated by wording the question in such a way as to induce a prevalence towards a certain answer from the respondent. For example, in polling support for a war, the questions:

• Do you support the attempt by the USA to bring freedom and democracy to other places in the world?
• Do you support the unprovoked military action by the USA?

will likely result in data skewed in different directions, although they are both polling about the support for the war.

Another way to do this is to precede the question by information that supports the "desired" answer. For example, more people will likely answer "yes" to the question "Given the increasing burden of taxes on middle-class families, do you support cuts in income tax?" than to the question "Considering the rising federal budget deficit and the desperate need for more revenue, do you support cuts in income tax?"

Overgeneralization

Overgeneralization is a fallacy occurring when a statistic about a particular population is asserted to hold among members of a group for which the original population is not a representative sample.

For example, suppose 100% of apples are observed to be red in summer. The assertion "All apples are red" would be an instance of overgeneralization because the original statistic was true only of a specific subset of apples (those in summer), which is not expected to representative of the population of apples as a whole.
A real-world example of the overgeneralization fallacy can be observed as an artifact of modern polling techniques, which prohibit calling cell phones for over-the-phone political polls. As young people are more likely than other demographic groups to have only a cell phone, rather than also having a conventional "landline" phone, young people are more likely to be liberal, and young people who do not own a landline phone are even more likely to be liberal than their demographic as a whole, such polls effectively exclude many voters who are more likely to be liberal.^[1]

Thus, a poll examining the voting preferences of young people using this technique could not claim to be representative of young peoples' true voting preferences as a whole without overgeneralizing, because the sample used is not representative of the population as a whole.
Overgeneralization often occurs when information is passed through nontechnical sources, in particular mass media.^[2]

Biased samples

Main article: Biased sample

Misreporting or misunderstanding of estimated error

If a research team wants to know how 300 million people feel about a certain topic, it would be impractical to ask all of them. However, if the team picks a random sample of about 1000 people, they can be fairly certain that the results given by this group are representative of what the larger group would have said if they had all been asked.

This confidence can actually be quantified by the central limit theorem and other mathematical results. Confidence is expressed as a probability of the true result (for the larger group) being within a certain range of the estimate (the figure for the smaller group). This is the "plus or minus" figure often quoted for statistical surveys. The probability part of the confidence level is usually not mentioned; if so, it is assumed to be a standard number like 95%.

The two numbers are related. If a survey has an estimated error of ±5% at 95% confidence, it also has an estimated error of ±6.6% at 99% confidence. ±x% at 95% confidence is always ±1.32x% at 99% confidence.

The smaller the estimated error, the larger the required sample, at a given confidence level.
at 95.4% confidence:
±1% would require 10,000 people.
±2% would require 2,500 people.
±3% would require 1,111 people.
±4% would require 625 people.
±5% would require 400 people.
±10% would require 100 people.
±20% would require 25 people.
±25% would require 16 people.
±50% would require 4 people.

Most people assume, because the confidence figure is omitted, that there is a 100% certainty that the true result is within the estimated error. This is not mathematically correct.

Many people may not realize that the randomness of the sample is very important. In practice, many opinion polls are conducted by phone, which distorts the sample in several ways, including exclusion of people who do not have phones, favoring the inclusion of people who have more than one phone, favoring the inclusion of people who are willing to participate in a phone survey over those who refuse, etc. Non-random sampling makes the estimated error unreliable.

On the other hand, many people consider that statistics are inherently unreliable because not everybody is called, or because they themselves are never polled^{[citation needed]}. Many people think that it is impossible to get data on the opinion of dozens of millions of people by just polling a few thousands. This is also inaccurate^{[citation needed]}. A poll with perfect unbiased sampling and truthful answers has a mathematically determined margin of error, which only depends on the number of people polled.
However, often only one margin of error is reported for a survey. When results are reported for population subgroups, a larger margin of error will apply, but this may not be made clear. For example, a survey of 1000 people may contain 100 people from a certain ethnic or economic group. The results focusing on that group will be much less reliable than results for the full population. If the margin of error for the full sample was 4%, say, then the margin of error for such a subgroup could be around 13%.
There are also many other measurement problems in population surveys.
The problems mentioned above apply to all statistical experiments, not just population surveys.

Further information: Opinion poll, Statistical survey

 False causality

Main article: Correlation does not imply causation

When a statistical test shows a correlation between A and B, there are usually five possibilities:

1. A causes B.
2. B causes A.
3. A and B both partly cause each other.
4. A and B are both caused by a third factor, C.
5. The observed correlation was due purely to chance.

The fifth possibility can be quantified by statistical tests that can calculate the probability that the correlation observed would be as large as it is just by chance if, in fact, there is no relationship between the variables. However, even if that possibility has a small probability, there are still the four others.
If the number of people buying ice cream at the beach is statistically related to the number of people who drown at the beach, then nobody would claim ice cream causes drowning because it's obvious that it isn't so. (In this case, both drowning and ice cream buying are clearly related by a third factor: the number of people at the beach).

This fallacy can be used, for example, to prove that exposure to a chemical causes cancer. Replace "number of people buying ice cream" with "number of people exposed to chemical X", and "number of people who drown" with "number of people who get cancer", and many people will believe you. In such a situation, there may be a statistical correlation even if there is no real effect. For example, if there is a perception that a chemical site is "dangerous" (even if it really isn't) property values in the area will decrease, which will entice more low-income families to move to that area. If low-income families are more likely to get cancer than high-income families (this can happen for many reasons, such as a poorer diet or less access to medical care) then rates of cancer will go up, even though the chemical itself is not dangerous. It is believed^[3] that this is exactly what happened with some of the early studies showing a link between EMF (electromagnetic fields) from power lines and cancer.^[4]

In well-designed studies, the effect of false causality can be eliminated by assigning some people into a "treatment group" and some people into a "control group" at random, and giving the treatment group the treatment and not giving the control group the treatment. In the above example, a researcher might expose one group of people to chemical X and leave a second group unexposed. If the first group had higher cancer rates, the researcher knows that there is no third factor that affected whether a person was exposed because he controlled who was exposed or not, and he assigned people to the exposed and non-exposed groups at random. However, in many applications, actually doing an experiment in this way is either prohibitively expensive, infeasible, unethical, illegal, or downright impossible. For example, it is highly unlikely that an IRB would accept an experiment that involved intentionally exposing people to a dangerous substance in order to test its toxicity. The obvious ethical implications of such types of experiments limit researchers' ability to empirically test causation.

 Proof of the null hypothesis

In a statistical test, the null hypothesis (H₀) is considered valid until enough data proves it wrong. Then H₀ is rejected and the alternative hypothesis (H_A) is considered to be proven as correct. By chance this can happen, although H₀ is true, with a probability denoted alpha, the significance level. This can be compared by the judicial process, where the accused is considered innocent (H₀) until proven guilty (H_A) beyond reasonable doubt (alpha).

But if data does not give us enough proof to reject H₀, this does not automatically prove that H₀ is correct. If, for example, a tobacco producer wishes to demonstrate that its products are safe, it can easily conduct a test with a small sample of smokers versus a small sample of non-smokers. It is unlikely that any of them will develop lung cancer (and even if they do, the difference between the groups has to be very big in order to reject H₀). Therefore it is likely—even when smoking is dangerous—that our test will not reject H₀. If H₀ is accepted, it does not automatically follow that smoking is proven harmless. The test has insufficient power to reject H₀, so the test is useless and the value of the "proof" of H₀ is also null.
This can—using the judicial analogue above—be compared with the truly guilty defendant who is released just because the proof is not enough for a guilty verdict. This does not prove the defendant's innocence, but only that there is not proof enough for a guilty verdict. In other words, "absence of evidence" does not imply "evidence of absence".

Data dredging

Main article: Data dredging

Data dredging is an abuse of data mining. In data dredging, large compilations of data are examined in order to find a correlation, without any pre-defined choice of a hypothesis to be tested. Since the required confidence interval to establish a relationship between two parameters is usually chosen to be 95% (meaning that there is a 95% chance that the relationship observed is not due to random chance), there is a thus a 5% chance of finding a correlation between any two sets of completely random variables. Given that data dredging efforts typically examine large datasets with many variables, and hence even larger numbers of pairs of variables, spurious but apparently statistically significant results are almost certain to be found by any such study.

Note that data dredging is a valid way of finding a possible hypothesis but that hypothesis must then be tested with data not used in the original dredging. The misuse comes in when that hypothesis is stated as fact without further validation.

Data manipulation

Informally called "fudging the data," this practice includes selective reporting (see also publication bias) and even simply making up false data.
Examples of selective reporting abound. The easiest and most common examples involve choosing a group of results that follow a pattern consistent with the preferred hypothesis while ignoring other results or "data runs" that contradict the hypothesis.
Psychic researchers have long disputed studies showing people with ESP ability. Critics accuse ESP proponents of only publishing experiments with positive results and shelving those that show negative results. A "positive result" is a test run (or data run) in which the subject guesses a hidden card, etc., at a much higher frequency than random chance
The deception involved in both cases is that the hypothesis is not confirmed by the totality of the experiments - only by a tiny, selected group of "successful" tests.
Scientists, in general, question the validity of study results that cannot be reproduced by other investigators. However, some scientists refuse to publish their data and methods.^[5]

Other fallacies

• N = 1 fallacy

Also, the post facto fallacy assumes that an event for which a future likelihood can be measured had the same likelihood of happening once it has already occurred. Thus, if someone had already tossed 9 coins and each has come up heads, people tend to assume that the likelihood of a tenth toss also being heads is 1023 to 1 against (which it was before the first coin was tossed) when in fact the chance of the tenth head is 1 to 1. This error has led, in the UK, to the false imprisonment of women for murder when the courts were given the prior statistical likelihood of a woman's 3 children dying from Sudden Infant Death Syndrome as being the chances that their already dead children died from the syndrome. This led to statements from Roy Meadow that the chances they had died of Sudden Infant Death Syndrome being millions to one against, convictions were then handed down in spite of the statistical inevitability that a few women would suffer this tragedy. Meadow was subsequently struck off the U.K. Medical Register for giving “erroneous” and “misleading” evidence, although this was later reversed by the courts.

Islam is Failing Europe

Organisers behind a British conference on Islam and evolution say they nearly had to cancel the event after receiving a torrent of opposition from Muslim students at one of the country’s top scientific universities, The Independent has leanred.

The Deen Institute, a Muslim debating forum which promotes critical thinking, had hoped to hold a conference entitled “Have Muslims misunderstood evolution?” early next year. Among the speakers invited to attend included Muslim scientists, imams who have promoted the compatibility of Islam and evolution as well as those who preach a form of Islamic creationism.

The initial plan was to hold the event next month at Imperial College London, one of the country’s foremost universities for scientific exploration and debate, in cooperation with the local Islamic student society. But the Deen Institute said it was forced to pull out when it became clear that opposition to the event from supporters of creationism began mounting. It is now being held without input from any Muslim student society at Logan Hall, a conference centre owned by the University of London.

“We eventually had to give up of getting any support from student societies because it was seen as simply too controversial,” Adam Deen, co-founder of the institute, told The Independent. Deen, who describes himself as a “conservative Muslim” who encourages critical thinking, said he was surprised to receive such opposition at a place of scientific study, particularly as he had made sure to invite all sides of the debate including those who preach creationism.

“It’s symptomatic of a bigger problem in the Muslim world where people representing practical Muslims have to be seen to be more literalist,” he said. “It’s almost like there’s an intellectual mafia movement who won’t allow any freedom of thought.”

Gaia hypothesis

On behalf of the Government and people of Kiribati I am pleased to welcome you to this web site which is designed to bring you information and updates on our situation in Kiribati.

You will be aware that our small country is facing critically difficult times with regard to climate change issues & its impact on our future. We hope the content and links from this site will assist you in understanding more clearly our situation. I am also pleased to refer you to the short video clip "Kiribati - A Call to the World" here on this page which very much represents the concerns and feelings of our people.

We thank you sincerely for your interest, and refer you to this site, or the contacts detailed here, if any further information is required. In closing may I offer our traditional Kiribati blessing—Te Mauri, Te Raoi ao Te Tabomoa—may good health, peace and prosperity be with you all.

Anote Tong
President of the Republic of Kiribati

Conformity and Mind Control

nothing exists outside the mind

Solipsism ( /ˈsɒlɨpsɪzəm/) is the philosophical idea that only one's own mind is sure to exist. The term comes from the Latin solus (alone) and ipse (self). Solipsism as an epistemological position holds that knowledge of anything outside one's own mind is unsure. The external world and other minds cannot be known, and might not exist outside the mind. As a metaphysical position, solipsism goes further to the conclusion that the world and other minds do not exist. As such it is the only epistemological position that, by its own postulate, is both irrefutable and yet indefensible in the same manner. Although the number of individuals sincerely espousing solipsism has been small, it is not uncommon for one philosopher to accuse another's arguments of entailing solipsism as an unwanted consequence, in a kind of reductio ad absurdum. In the history of philosophy, solipsism has served as a skeptical hypothesis.

Wahrnehmung ist Falschnehmung

The earth is as old as we are, no older. How could it be older? Nothing exists except through human consciousness. Before man there was nothing. After man, if he could come to an end, there would be nothing. Outside man there is nothing.

O'Brian (George Orwell in 1984)

tit for tat

Nice Guys Finish First (BBC Horizon television series) is a 1986 documentary by Richard Dawkins which discusses selfishness and cooperation, arguing that evolution often favors co-operative behaviour, and focusing especially on the tit for tat strategy of the prisoner's dilemma game. The film is approximately 45 minutes long and was produced by Jeremy Taylor.

The twelfth chapter in Dawkins' book The Selfish Gene (added in the second edition, 1989) is also named Nice Guys Finish First and explores similar material.

This strategy is dependent on four conditions, which have allowed it to become the most successful strategy for the iterated prisoner's dilemma:^[1]

1. Unless provoked, the agent will always cooperate
2. If provoked, the agent will retaliate
3. The agent is quick to forgive
4. The agent must have a good chance of competing against the opponent more than once.

In the last condition, the definition of "good chance" depends on the payoff matrix of the prisoner's dilemma. The important thing is that the competition continues long enough for repeated punishment and forgiveness to generate a long-term payoff higher than the possible loss from cooperating initially.

A fifth condition applies to make the competition meaningful: if an agent knows that the next play will be the last, it should naturally defect for a higher score. Similarly if it knows that the next two plays will be the last, it should defect twice, and so on. Therefore the number of competitions must not be known in advance to the agents.

Generally, in game theory, effectiveness of a strategy is measured under the assumption that each player cares only about him or herself. (Thus, the game-theory measure of effectiveness is impractical in many real life situations where players do have a vested interest in, or an altruistic compassion towards, other players.) Furthermore, game-theory effectiveness is usually measured under the assumption of perfect communication, where it is assumed that a player never misinterprets the intention of other players. By this game-theory definition of effectiveness tit for tat was superior to a variety of alternative strategies, winning in several annual automated tournaments against (generally far more complex) strategies created by teams of computer scientists, economists, and psychologists. Some game theorists informally believe the strategy to be optimal, although no proof is presented.

In some competitions tit for tat was not the most effective strategy, even under the game-theory definition of effectiveness. However, tit for tat would have been the most effective strategy if the average performance of each competing team were compared. The team which recently won over a pure tit for tat team outperformed it with some of their algorithms because they submitted multiple algorithms which would recognize each other and assume a master and slave relationship (one algorithm would "sacrifice" itself and obtain a very poor result for the other algorithm to be able to outperform tit for tat on an individual basis, but not as a pair or group). This "group" victory illustrates one of the important limitations of the Prisoner's Dilemma in representing social reality, namely, that it does not include any natural equivalent for friendship or alliances. The advantage of tit for tat thus pertains only to a Hobbesian world of so-called rational solutions (with perfect communication), not to a world in which humans are inherently social.






However, that this winning solution does not work effectively against groups of agents running tit for tat illustrates the strengths of tit for tat when employed in a team (that the team does better overall, and all the agents on the team do well individually, when every agent cooperates).


Proving that a new approach can secure victory in a classic strategy game, a team from England's Southampton University has won the 20th-anniversary Iterated Prisoner's Dilemma competition, toppling the long-term winner from its throne. The Southampton group, whose primary research area is software agents, said its strategy involved a series of moves allowing players to recognize each other and act cooperatively.
The Prisoner's Dilemma is a game-theory problem for two players. As typically described, two accomplices are arrested and separated for interrogation by the police, who give each the same choice: confess to authorities (defect) or remain silent (cooperate). If one defects and the other cooperates, the defector walks free and the cooperator gets 10 years in jail. If both cooperate, both get six months. If both defect, both get six years. Neither suspect knows the other's choice. "The Prisoner's Dilemma is this canonical problem of how to get cooperation to emerge from selfish agents," said Nick Jennings, a professor in computer science at Southampton University and leader of the winning team along with his Ph.D. student, Gopal Ramchurn. "People are very keen on it because they can see so many parallels in real life." Before Southampton came along, a strategy called Tit for Tat had a consistent record of winning the game. Under that strategy, a player's first move is always to cooperate with other players. Afterward, the player echoes whatever the other players do.

The strategy is similar to the one nuclear powers adopted during the Cold War, each promising not to use its weaponry so long as the other side refrained from doing so as well. The 20th-anniversary competition was the brainchild of Graham Kendall, a lecturer in the University of Nottingham's School of Computer Science and Information Technology and a researcher in game theory, and was based on the original 1984 competition run by a University of Michigan political scientist, Robert Axelrod.

The Iterated Prisoner's Dilemma is a version of the game in which the choice is repeated over and over again and in which the players can remember their previous moves, allowing them to evolve a cooperative strategy. The 2004 competition had 223 entries, with each player playing all the other players in a round robin setup. Because Axelrod's original competition was run twice, Kendall will run a second competition in April 2005, for which he hopes to attract even more entries. Teams could submit multiple strategies, or players, and the Southampton team submitted 60 programs. These, Jennings explained, were all slight variations on a theme and were designed to execute a known series of five to 10 moves by which they could recognize each other. Once two Southampton players recognized each other, they were designed to immediately assume "master and slave" roles -- one would sacrifice itself so the other could win repeatedly. If the program recognized that another player was not a Southampton entry, it would immediately defect to act as a spoiler for the non-Southampton player. The result is that Southampton had the top three performers -- but also a load of utter failures at the bottom of the table who sacrificed themselves for the good of the team. Another twist to the game was the addition of noise, which allowed some moves to be deliberately misrepresented. In the original game, the two prisoners could not communicate. But Southampton's design lets the prisoners do the equivalent of signaling to each other their intentions by tapping in Morse code on the prison wall. Kendall noted that there was nothing in the competition rules to preclude such a strategy, though he admitted that the ability to submit multiple players means it's difficult to tell whether this strategy would really beat Tit for Tat in the original version. But he believes it would be impossible to prevent collusion between entrants.

"Ultimately," he said, "what's more important is the research." In Jennings' case, the real interest is agents. "What's interesting from our point of view," he said, "was to test some ideas we had about teamwork in general agent systems, and this detection of working together as a team is a quite fundamental problem. What was interesting was to see how many colluders you need in a population. It turns out we had far too many -- we would have won with around 20." Jennings is also interested in testing the strategy on an evolutionary variant of the game in which each player plays only its neighbors on a grid. If your neighbors do better than you do, you adopt their strategy. "Our initial results tell us that ours is an evolutionarily stable strategy -- if we start off with a reasonable number of our colluders in the system, in the end everyone will be a colluder like ours," he said. The winners don't get much -- an unexpected $50 check and a small plaque. But, says Kendall, "Everybody in our field knows the name of Anatol Rapoport, who won the Axelrod competition. So if you can win the 20th-anniversary one, in our field there's a certain historical significance."