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Can't look away
Many years ago I read to my daughter a children's book in which a little girl learning to ride a bicycle keeps running into objects like trees and lampposts. A bicycle instructor explains to her that when you become too fixated on an obstacle it exerts a strong psychological pull, so that the very exigency of evading it leads to a crash.
I used to wonder whether this was a real phenomenon. I don't anymore…
Actually, I've long thought the second Iraq War was an example of the same phenomenon. There was no possibility that there wouldn't be a war, because once they'd started to consider it Bush and Blair couldn't bare not to see how it would turn out.
Author steinsaltzPosted on December 13, 2020 Categories Personal reflection, PoliticsTags Brexit, children, psychology, UK politics, warLeave a comment on Can't look away
The first principle of statistical inference
When I first started teaching basic statistics, I thought about how to explain the importance of statistical hypothesis testing. I focused on a textbook example (specifically, Freedman, Pisani, Purves Statistics, 3rd ed., sec 28.2) of a data set that seems to show more women being right-handed than men. I pointed out that we could think of many possible explanations: Girls are pressured more to conform, women are more rational — hence left-brain-centred. But before we invest too much time and credibility in abstruse theories to explain the phenomenon, we should first make sure that the phenomenon is real, that it's not just the kind of fluctuation that could happen by accident. (It turns out that the phenomenon is real. I don't know if either of my explanations is valid, or if anyone has a more plausible theory.)
I thought if this when I heard about the strange Oxford-AstraZeneca vaccine serendipity that was announced this week. The third vaccine success announced in as many weeks, the researchers announced that they had found about a 70% efficacy, which is good, but not nearly as impressive as the 95% efficacy of the mRNA vaccines announced earlier in the month. But the strange thing was, they found that a subset of the test subjects who received only a half dose at the first injection, and a full dose later, showed a 90% efficacy. Experts have been all over the news media trying to explain how some weird idiosyncrasies of the human immune system and the chimpanzee adenovirus vector could make a smaller dose more effective. Here's a summary from Science:
Researchers especially want to know why the half-dose prime would lead to a better outcome. The leading hypothesis is that people develop immune responses against adenoviruses, and the higher first dose could have spurred such a strong attack that it compromised the adenovirus' ability to deliver the spike gene to the body with the booster shot. "I would bet on that being a contributor but not the whole story," says Adrian Hill, director of Oxford's Jenner Institute, which designed the vaccine…
Some evidence also suggests that slowly escalating the dose of a vaccine more closely mimics a natural viral infection, leading to a more robust immune response. "It's not really mechanistically pinned down exactly how it works," Hill says.
Because the different dosing schemes likely led to different immune responses, Hill says researchers have a chance to suss out the mechanism by comparing vaccinated participants' antibody and T cell levels. The 62% efficacy, he says, "is a blessing in disguise."
Others have pointed out that the populations receiving the full dose and the half dose were substantially different: The half dose was given by accident to a couple of thousand subjects at the start of the British arm of the study. These were exclusively younger, healthier individuals, something that could also explain the higher efficacy, in a less benedictory fashion.
But before we start arguing over these very interesting explanations, much less trying to use them to "suss out the mechanisms" the question they should be asking is, is the effect real? The Science article quotes immunologist John Moore asking "Was that a real, statistically robust 90%?" To ask that question is to answer it resoundingly: No.
They haven't provided much data, but the AstraZeneca press release does give enough clues:
One dosing regimen (n=2,741) showed vaccine efficacy of 90% when AZD1222 was given as a half dose, followed by a full dose at least one month apart, and another dosing regimen (n=8,895) showed 62% efficacy when given as two full doses at least one month apart. The combined analysis from both dosing regimens (n=11,636) resulted in an average efficacy of 70%. All results were statistically significant (p<=0.0001)
Note two tricks they play here. First of all, they give those (n=big number) which makes it seem reassuringly like they have an impressively big study. But these are the numbers of people vaccinated, which is completely irrelevant for judging the uncertainty in the estimate of efficacy. The reason you need such huge numbers of subjects is so that you can get moderately large numbers where it counts: the number of subjects who become infected. Further, while it is surely true that the "results" were highly statistically significant — that is, the efficacy in each individual group was not zero — this tells us nothing about whether we can be confident that the efficacy is actually higher than what has been considered the minimum acceptable level of 50%, or — and this is crucial for the point at issue here — whether the two groups were different from each other.
They report a total of 131 cases. They don't say how many cases were in each group, but if we assume that there were equal numbers of subjects getting the vaccine and the treatment in all groups then we can back-calculate the rest. We end up with 98 cases in the full-dose group (of which 27 received the vaccine) and 33 cases in the half-dose group, of which 3 received the vaccine. Just 33! Using the Clopper-Pearson exact method, we obtain 90% confidence intervals of (.781,.975) for the efficacy of the half dose and (.641, .798) for the efficacy of the full dose. Clearly some overlap there, and not much to justify drawing substantive conclusions from the difference between the two groups — which may actually be zero, or close to 0.
Author steinsaltzPosted on November 26, 2020 Categories PoliticsTags public health, science and society, statistics1 Comment on The first principle of statistical inference
The return of quota sampling
Everyone knows about the famous Dewey Defeats Truman headline fiasco, and that the Chicago Daily Tribune was inspired to its premature announcement by erroneous pre-election polls. But why were the polls so wrong?
The Social Science Research Council set up a committee to investigate the polling failure. Their report, published in 1949, listed a number of faults, including disparaging the very notion of trying to predict the outcome of a close election. But one important methodological criticism — and the one that significantly influenced the later development of political polling, and became the primary lesson in statistics textbooks — was the critique of quota sampling. (An accessible summary of lessons from the 1948 polling fiasco by the renowned psychologist Rensis Likert was published just a month after the election in Scientific American.)
Serious polling at the time was divided between two general methodologies: random sampling and quota sampling. Random sampling, as the name implies, works by attempting to select from the population of potential voters entirely at random, with each voter equally likely to be selected. This was still considered too theoretically novel to be widely used, whereas quota sampling had been established by Gallup since the mid-1930s. In quota sampling the voting population is modelled by demographic characteristics, based on census data, and each interviewer is assigned a quota to fill of respondents in each category: 51 women and 49 men, say, a certain number in the age range 21-34, or specific numbers in each "economic class" — of which Roper, for example, had five, one of which in the 1940s was "Negro". The interviewers were allowed great latitude in filling their quotas, finding people at home or on the street.
In a sense, we have returned to quota sampling, in the more sophisticated version of "weighted probability sampling". Since hardly anyone responds to a survey — response rates are typically no more than about 5% — there's no way the people who do respond can be representative of the whole population. So pollsters model the population — or the supposed voting population — and reweight the responses they do get proportionately, according to demographic characteristics. If Black women over age 50 are thought to be equally common in the voting population as white men under age 30, but we have twice as many of the former as the latter, we count the responses of the latter twice as much as the former in the final estimates. It's just a way of making a quota sample after the fact, without the stress of specifically looking for representatives of particular demographic groups.
Consequently, it has most of the deficiencies of a quota sample. The difficulty of modelling the electorate is one that has gotten quite a bit of attention in the modern context: We know fairly precisely how demographic groups are distributed in the population, but we can only theorise about how they will be distributed among voters at the next election. At the same time, it is straightforward to construct these theories, to describe them, and to test them after the fact. The more serious problem — and the one that was emphasised in the commission report in 1948, but has been less emphasised recently — is in the nature of how the quotas are filled. The reason for probability sampling is that taking whichever respondents are easiest to get — a "sample of convenience" — is sure to give you a biased sample. If you sample people from telephone directories in 1936 then it's easy to see how they end up biased against the favoured candidate of the poor. If you take a sample of convenience within a small demographic group, such as middle-income people, then it won't be easy to recognise how the sample is biased, but it may still be biased.
For whatever reason, in the 1930s and 1940s, within each demographic group the Republicans were easier for the interviewers to contact than the Democrats. Maybe they were just culturally more like the interviewers, so easier for them to walk up to on the street. And it may very well be that within each demographic group today Democrats are more likely to respond to a poll than Republicans. And if there is such an effect, it's hard to correct for it, except by simply discounting Democrats by a certain factor based on past experience. (In fact, these effects can be measured in polling fluctuations, where events in the news lead one side or the other to feel discouraged, and to be less likely to respond to the polls. Studies have suggested that this effect explains much of the short-term fluctuation in election polls during a campaign.)
Interestingly, one of the problems that the commission found with the 1948 polling with relevance for the Trump era was the failure to consider education as a significant demographic variable.
All of the major polling organizations interviewed more people with college education than the actual proportion in the adult population over 21 and too few people with grade school education only.
Author steinsaltzPosted on November 11, 2020 Categories Politics, TechnicalTags history of science, polling, statistics, US history, US politicsLeave a comment on The return of quota sampling
Exotic animal farming
I remember when people were muttering about Covid-19 being all the fault of the weird Chinese and their weird obsession with eating weird animals like pangolins.
So now we have a second version of Covid, that may start a completely novel pandemic, and it comes from the weird Europeans and their weird obsession with wearing the fur of weird animals like minks. Apparently, it was well known that Covid was spreading widely among the minks, but the animals were too valuable to give up on, so they tried to get away with just culling the obviously sick ones. And now we can just hope that they can get the new plague out of Denmark under control before it becomes a second pandemic.
But the people who advocate just giving up on eating and wearing animals are still treated as something between dreamy mystics and lunatics…
Author steinsaltzPosted on November 11, 2020 Categories Politics, SocietyTags animals, China, covid-19, foodLeave a comment on Exotic animal farming
Trump's dilemma
Did he recover from his covid-19 infection because he is a perfect physical specimen? Or because of the brilliant cure that he invented (and that Biden definitely wouldn't have allowed!), as he explains in this video.
In which he raves like an addled junky about the amazing shit he got, and how everyone should try some.
Author steinsaltzPosted on October 9, 2020 Categories PoliticsTags medicine, rhetoric, Trump, US politicsLeave a comment on Trump's dilemma
Less than zero, part 2
In a long-ago post I wrote about how huge debts don't make you poor, and illustrated this with the story of real-estate mogul Donald Trump. Negative large fortunes are closer to positive large fortunes than either is to zero. (I later had to correct my interpretation later, on discovering that the counterintuitive behaviour of Trump's creditors was largely a reflection of their involvement in money laundering.)
Now we learn from the N Y Times that Trump has been paying $750 in federal income tax each year as president. Presumably that's just an arbitrary number that he made up so that he could say it wasn't zero. (Apparently even Trump has some limits to his his explicit lying.)
But here's the thing: $750 is probably worse than $0. People have been assuming he wasn't paying taxes. It sounds like a general insult. $750 is too specific (as well as being too small). The number becomes a shorthand for his tax-dodging, as well as inviting people to compare their own tax bills to Trump's.
This demonstrates again how absurdly miserly Donald Trump, above and beyond his criminality. He had to choose an amount to pay purely for the symbolism of possibly needing to tell average Americans how much he had paid. He could certainly have afforded not to choose an amount large enough that even Americans of modest means would find risible. At least four figures…
Author steinsaltzPosted on October 2, 2020 Categories PoliticsTags economics, taxes, Trump, US politicsLeave a comment on Less than zero, part 2
The opposite of a superficial lie
"The opposite of a fact is a falsehood. But the opposite of a profound truth may very well be another profound truth."
The news media have gotten themselves tangled up, from the beginning of the Trump era, in the epistemological question of whether any statement can objectively be called a lie. Yes, Trump says things that are untrue, that contradict objectively known facts, but are they lies? Does he have the appropriate mens rea to lie, the intention to deceive, or is that just a partisan insult?
The opposite problem has gotten too little attention. Just because Donald Trump says something that corresponds to objective facts, one cannot infer that he is speaking the truth. (We don't really have a word in English to correspond to the opposite of lie, in this dichotomy.) A good example is the controversy over Trump's private and public comments on the incipient Coronavirus pandemic in February and March of this year. On February 7, 2020, Trump told Woodward
You just breathe the air and that's how it's passed. And so that's a very tricky one. That's a very delicate one. It's also more deadly than even your strenuous flus.
This is quite an accurate statement, and also very different than what he was saying publicly. On February 10 he said, in a campaign speech,
I think the virus is going to be — it's going to be fine.
And February 26 in an official White House pandemic task force briefing:
The 15 [case count in the U.S.] within a couple of days is going to be down to close to zero. … This is a flu. This is like a flu.
When you see that someone has been saying one thing in public and something completely different in private, it's natural to interpret the former as lying and the latter as the secret truth — particularly when, as in this case, the private statement is known to be, in fact, true, and the public statement false. And particularly when the speaker later says
I wanted to always play it down. I still like playing it down, because I don't want to create a panic.
With Trump, though, this interpretation is likely false.
The thing is, while his statement of February 7 was true, he could not have known it was true. No one knew it was true. We can see any number of statements by responsible public-health officials making similar statements at the time. For example, Anthony Fauci on February 19:
Fauci doesn't want people to worry about coronavirus, the danger of which is "just minuscule." But he does want them to take precautions against the "influenza outbreak, which is having its second wave."
"We have more kids dying of flu this year at this time than in the last decade or more," he said. "At the same time people are worrying about going to a Chinese restaurant. The threat is (we have) a pretty bad influenza season, particularly dangerous for our children."
And it's not just Americans under the thumb of Trump. February 6, the day before Trump's remark to Woodward, the head of the infectious disease clinic at a major Munich hospital, where some of the first German Covid-19 patients were being treated, told the press that "Corona is definitely not more dangerous than influenza," and criticised the panic that was coming from exaggerated estimates of mortality rates.
Researchers were posting their data and models in real time, but there just wasn't enough understanding possible then. This is the kind of issue where the secret information that a government has access to is of particularly limited value.
So how are we to interpret Trump's statements? I think the key is that Trump is not a liar per se, he is a conman and a bullshitter, someone to whom the truth of his statements is completely irrelevant.
In early February he probably did receive a briefing where the possibility that the novel coronavirus was highly lethal and airborne was raised as one possibility, as well as the possibility that it was mild and would disappear on its own. .In talking to elite journalist Bob Woodward he delivered up the most frightening version, not because he believed it was true, but because it seemed most impressive, making him seem like the mighty keeper of dangerous secrets. When talking to the public he said something different, because he had other motives. It's purely coincidence that what he said in private turned out to be true.
It would be poetic justice of Trump were to be damaged by the bad luck of one time accidentally having told the truth.
Author steinsaltzPosted on September 12, 2020 September 13, 2020 Categories PoliticsTags covid-19, journalism, Trump, truth, US politics1 Comment on The opposite of a superficial lie
Political football
Guardian: The shadow Northern Ireland secretary, Louise Haigh, accused the government of using the region as a "political football".
Too generous. Calling it a "football" suggests the government has some goal in mind.
Author steinsaltzPosted on September 8, 2020 Categories PoliticsTags conservatives, metaphors, UK politicsLeave a comment on Political football
The model didn't fail us, we failed the model
THE ALGORITHM. It's all anyone can talk about, when they're talking about universities these days. Illustrative of the unique ability of the current UK government to take a challenging societal problem in hand, and transform it into a flaming chaos that simultaneously exacerbates divisions and satisfies no one.
In this case, it's about the assignment of marks in A-levels (18 year-olds) released last week, and GCSEs (16-year-olds) still ahead this week. Scotland had its own small version of the fiasco that played out earlier in the week for their own Scottish Higher exams, but the UK government, responsible for English A-levels, managed not only not to learn from the Scottish situation and change course early, it managed to parlay the political challenge into a systemic disaster for higher education that will now roll on for at least the next year or two.
Like any great governing disaster, this one has been years in the making. Pupils doing A levels used to have intermediate exams — AS levels — after the first year of their two-year course, as well as significant amounts of coursework that counted for a substantial portion of their final marks. AS levels were progressively eliminated and coursework reduced over the past decade in England (but not Wales), as the Conservatives seem to have believed that todays pupils were being inappropriately coddled by having too little stress and uncontrollable randomness in their lives, leaving several weeks of exams right at the end of their course as the only determinant of the marks that would decide high-stakes competition for university places. Then they cancelled the exams, in a panicked response to the first wave of Covid-19. Leaving them with nothing.
Weirdly, it's not as though they don't have frequent exams during their school (and university) time. But these exams are called "mock exams", and don't count for anything in the end.
Which brings us to THE ALGORITHM. How do you assign marks to students when you don't have any exams? Teachers have quite a lot of information, even if it doesn't formally count for anything in the regular process. (Weirdly, teachers are regularly expected to produce "predicted grades" based on mock exams, coursework, and general impressions, because the official marks arrive too late for university admissions.) But on average they tend to be overly optimistic — or, one might also say, either generous or strategic, since the university admission offer that results from an overpredicted A-level grade is not necessarily withdrawn when the exam result exceeds it, whereas the university place that is lost from an underprediction is almost impossible to make good.
If you were a mindless machine-learning bot trying to optimise the accuracy of prediction of missing marks in an overall minimum-mean-error way, you would take data about each student's family income, ethnicity, sex, parents' occupations, and region, all of which are likely to be correlated to exam scores. But that would seem outrageously biased: Why should the young person with wealthy parents get higher A-level marks than the one with poor parents, after they had the same mock exam grades? The machine-learning answer is, because that's what's happened with real grades in the past. The wealthy family is likely to provide more support, maybe tutors, a more stable environment for studying for the exams. The child of the poor family may have been working hard since year 12, but there's a much higher chance that the family would have had a crisis — maybe a parent losing a job, illness, homelessness — that would have distracted from exam preparation and led to underperformance at the exam. And since that might have happened in reality, that needs to be reflected in our optimal prediction algorithm.
But that looks bad, so the Ofqual boffins used past school performance as a proxy. Effectively, they said that each school gets the same marks this year that they got last year. Teacher evaluations were used to rank the students in each subject, to decide which students get the school's quota of A*'s, etc. If you made the bad life choice to go to a low-performing school where no one in living memory has scored better than B in chemistry, then B is the ceiling for your marks, no matter what scores you may personally have been achieving on your mockeries.
Averaged over the whole population of English students your misfortune is just a small blemish on an overall excellent prediction.
It's a good illustration of the problems of ethical machine learning. People say, if you don't want your algorithm to be biased based on gender, don't include gender information in the dataset. But if you instead include height information, say, the algorithm will learn all the gender bias in the training set and assign it to the height variable.
Just to rub salt in the wounds, there was an extra fillip for students in small — heavily private — schools: Since average performance fluctuates more in small groups, courses with 15 or fewer students had their (generally higher) teacher predictions more heavily weighted in their final marks, and those with 5 or fewer received their teacher predictions unfiltered.
Now, this way of using past school performance seems… surprising, to those of us who have been involved in UK university admissions in the past, given the extent of government and public outrage every year when the elite universities once again draw their intake from a very small sliver of UK secondary schools, predominantly private schools. You might think that this outrage reflects a belief that the differences in average exam performance, that drive most of the differential in university admissions, are unfair, that they do not accurately represent student ability, performance, and potential. If you believed that, you might propose a very different way of using school performance to assign marks, namely: Every school gets the same proportion of A*, A, B, etc., to be allocated within each subject according to the teacher rankings. I'm not advocating this method, but it is no more extreme, in its own way, than the application of past school performance that was actually implemented.
To the extent that A-level marks are primarily a tool for sorting graduates for university admissions, this would function somewhat similarly to the practice of some US states, of guaranteeing admission to their state universities to a certain percentile of every high school in the state. This leverages housing and school segregation to benefit equality, as opposed to the opposite.
The fact that my algorithm seems obviously unfair to individuals, while the other algorithm was seen as not only credible but actually self-evident, reflects nothing but naked ideology about the nature of class.
Education minister (a position whose relationship to that of education secretary confuses me) Nick Gibb responded to the fiasco thus:
So the model itself was fair, it was very popular, it was widely consulted upon. The problem arose in the way in which the three phases of the application of that model – the historic data of the school, the prior attainment of the cohort of pupils at the school, and then the national standard correction – it's that element of the application of the model that I think there is a concern."
The minister went on: "The application of the model is a regulatory approach and it's the development of that that emerged on the Thursday when the algorithm was published. And at that stage it became clear that there were some results that were being published on Thursday and Friday that were just not right and they were not what the model had intended."
The poor misunderstood beast. It meant well…
Author steinsaltzPosted on August 27, 2020 Categories Politics1 Comment on The model didn't fail us, we failed the model
Count no statue happy…
Count no man happy till he dies.
Sophocles, Oedipus the King (trans. Robert Fagles)
Must no one at all, then, be called happy while he lives; must we, as Solon says, see the end? Even if we are to lay down this doctrine, is it also the case that a man is happy when he is dead? […] for both evil and good are thought to exist for a dead man, as much as for one who is alive but not aware of them; e.g. honours and dishonours and the good or bad fortunes of children and in general of descendants.
Aristotle, Nichomachean Ethics, Book 1 (trans. W D Ross)
In all of the discussion of racist statues one fundamental point is rarely mentioned: Above all, public statues represent the unwillingness of "great men" to simply go away. Those who bestrode their narrow world like a Colossus are loath to let death remove them from the scene, so like the stuffed dodo in a diorama they have their effigies propped up in the public square.
While they lived they received the adulation of the crowds, and the opprobrium of their opponents. If the great one's supporters need a public icon as a focus for their devotions, the icon will have to continue to participate in the hurly-burly of public life, including the scrutiny of their lives and deeds brought on by shifting ethical standards. If Winston Churchill were alive today he would rightly have paint and rotten tomatoes flung at him by those appalled at his racist ideas and actions. Reasonable can believe that his near-genocidal actions in Bengal, among others places inhabited by darker-skinned people, are more significant than a few well-crafted speeches that bucked up the spirits of the Island Race. Reasonable people did think so during his life. The place where one is beyond praise or blame is called the grave, and no one is suggesting disinterring WC's bones — though an earlier generation of Tories did exactly that with Oliver Cromwell, after the tide of history turned against him.
His supporters are welcome to hide his statues away in private shrines, or public museums. If you put them up in public you have to accept that people are going to continue to engage with them. Sometimes angrily. Sometimes disorderly.
Author steinsaltzPosted on July 5, 2020 Categories History, PoliticsTags ethics, literature, statues, UK historyLeave a comment on Count no statue happy…


Hey all, new user, happy to be here. I am a CNC machinist / programmer for a living, and enjoy the geometric and logic problems that come with the job. In my free time I wrench on anything with a motor, and enjoy some PC gaming when possible.


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Come As You Are & The Come As You Are Workbook
The extremely popular Come As You Are — Emily Nagoski's master class in the science of sex — now has a helpful workbook companion to help guide you into the best sex life ever!
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An essential exploration of why and how women's sexuality works—based on groundbreaking research and brain science—that will radically transform your sex life into one filled with confidence and joy.
Researchers have spent the last decade trying to develop a "pink pill" for women to function like Viagra does for men. So where is it? Well, for reasons this book makes crystal clear, that pill will never exist—but as a result of the research that's gone into it, scientists in the last few years have learned more about how women's sexuality works than we ever thought possible, and Come as You Are explains it all.
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Revised and updated throughout, including all-new chapters specifically for beginners and for women giving anal pleasure to men, The Ultimate Guide to Anal Sex for Women is a comprehensive and creative guide to anal pleasure.
The Ins and Outs of Gay Sex
Here, at last, is reliable, comprehensive information on a wide spectrum of gay medical concerns, written by an eminent surgeon and recognized authority on gay health issues.
With up-to-date facts, interviews, and case studies from the author's practice, this book goes far beyond HIV concerns, combining a complete education about the safe and pleasurable practices of male-male sexuality with a comprehensive medical volume.
Sex Is Fun! by Kidder Kapers
Sex Is Fun! Creative Ideas for Exciting Sex by Kidder Kapers
A fully illustrated, interactive, and completely original sex manual, combining the innovative look of a graphic novel with nonfiction advice and activities for fearless fun in bed!
Healing Painful Sex
A Woman's Guide to Confronting, Diagnosing, and Treating Sexual Pain
Millions of women suffer from sexual and pelvic pain in America today, yet it is frequently misdiagnosed—or not diagnosed at all.
In Healing Painful Sex, Deborah Coady, MD and Nancy Fish use their combined professional expertise as a doctor and therapist who specialize in sexual pain to provide readers with an understanding of its many causes and how to treat them, from both a physical and psychological standpoint.
Because you deserve to experience sex without pain.
Miss Vera's Cross-Dress for Success
A Resource Guide for Boys who Want to be Girls
By Veronica Vera
Whether you're dressing up for Halloween or choosing a new lifestyle, let Miss Vera be your guide. Looking for an open-nipple bullet bra or a sexy peignoir? Some tips on hair removal or makeup? Miss Vera will point you in the right direction.
A Hand In The Bush: The Fine Art of Vaginal Fisting
Vaginal fisting – the intimate, potent sexual act of gradually inserting the entire hand into the vagina is an increasingly popular form of play among lesbians, bisexuals and heterosexuals alike. Now, for the first time, an experienced fister and fistee explains in detail how to fist with the greatest possible safety and pleasure!
Extensively illustrated, this long-awaited guide by Deborah Addington has been approved by three fisting-positive physicians and by many experienced practitioners. Also includes an eye-opening section of anecdotes and poetry by fisting-lovers, plus an extensive resource guide.
A must-have "handbook" for the sexually explorative!
The Explorer's Guide to Planet Orgasm
The Explorer's Guide to Planet Orgasm is an unprecedentedly easy, fun way to expand the definition of orgasm and find new ways to reach it. by Annie Sprinkle, Ph.D and Beth Stephens, Ph.D
Fumbling Towards Repair
Fumbling Toward Repair is a workbook by Mariame Kaba and Shira Hassan that includes reflection questions, skill assessments, facilitation tips, helpful definitions, activities, and hard-learned lessons intended to support people who have taken on the coordination and facilitation of formal community accountability processes to address interpersonal harm & violence.
Not for beginners! This workbook is intended for people with experience in community accountability work, whether as formal or informal facilitators, mediators, and survivors' support people. It's the book the creators wish they'd had when they were first starting out.
The exercises focus on self-accountability, assessing and growing your own skills, deciding whether or not to get involved, troubleshooting common problems, and improving your grasp of the technical nuts and bolts of accountability. Includes exercises to do on your own, with survivors, with perpetrators, and with your team.
Packed full of stories, perspectives from many people and situations, example documents, and more. This resource is deeply thoughtful, practical, and full of heart for the people who find their calling is to try to help mend the most broken relationships.
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