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common-myths-debunked [2025/12/21 20:57] – created valahcommon-myths-debunked [2025/12/25 14:57] (current) valah
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-====== Statistical Sleight of HandHow Misrepresentation Distorts Prison Statistics ======+====== The "Trans Women Offend Like Men" Myth: Prison Data Manipulation ======
  
-===== The Transmisic Claim =====+===== The Transmisic Claims =====
  
-"Analysis of Ministry of Justice (MoJ) data from 2019/2020 indicated that approx 59% of trans women in prison had at least one conviction for a sexual offence against 17% of other men in prison."+**Claim 1**: "The data seems to say that trans women offend in an identical way to men."
  
-Or something similar.+**Claim 2**: "Trans women are convicted of sexual offenses at rates of about 1,177 per million—higher than men's 490 per million."
  
-===== The Numbers Behind Those Percentages =====+**Any claim suggesting**: 
 +  * Over-representation of trans women in prisons for "sexual offenses" 
 +  * Trans women are per-capita more likely to commit "sexual offenses" 
 +  * Trans women pose a greater risk/threat to cisgender people 
 +  * Based on prison composition statistics or "The Swedish Study" 
 + 
 +**All of these claims** rely on the same statistical manipulation techniques and misrepresentations of studies and fact, which we'll break down below. 
 + 
 + 
 +===== What the Prison Data Actually Shows =====
  
 ^ Population ^ Total ^ Sex Offenders ^ Percentage ^ ^ Population ^ Total ^ Sex Offenders ^ Percentage ^
 | Trans women prisoners | 129 | 76 | 58.9% | | Trans women prisoners | 129 | 76 | 58.9% |
-| Cisgender men prisoners | ~78,781 | ~13,234 | 16.8% |+| Cisgender men prisoners | 78,781 | 13,234 | 16.8% | 
 +| Cisgender women prisoners | 3,812 | 125 | 3.3% |
  
-===== What This Actually Shows =====+===== The Sleight of Hand: Several Tricks in One =====
  
-  * 76 trans women sex offenders in prison +==== Trick #1: Comparing Percentages of Wildly Different Groups ====
-  * ~13,234 cisgender men sex offenders in prison+
  
-**The percentage comparison hides the real disparity:** You're comparing 76 to 13,234—a completely different scale.+You're comparing **76 people** to **13,234 people** using percentages. This hides the scale.
  
-For this reason, things like per capita and ratio/percentage comparisons are often prone to over-representation and are therefore misleading. There is nuance here: there is no denying an over-representation; however, when the numbers are so disparate, the over-representation doesn't matter. It may be statistically significant, but it is practically irrelevant.+**The Classroom Analogy**
  
-===== The Classroom Analogy =====+  * Classroom A: 129 students, 76 like chocolate 58.9% 
 +  * Classroom B: 78,781 students, 13,234 like chocolate 16.8%
  
-Imagine two classrooms:+Does Classroom A "like chocolate more"? No. Classroom B has **174 times more chocolate lovers**—it just looks smaller as a percentage because the classroom is massive.
  
-  * **Classroom A:** 129 students total, 76 like chocolate 58.9% +==== Trick #2Ignoring Who Gets Counted ====
-  * **Classroom B:** 78,781 students total, 13,234 like chocolate 16.8%+
  
-If you say "Classroom A likes chocolate more!you'd be wrong. Classroom B has way more chocolate lovers in absolute numbers; it just looks smaller as a percentage because the classroom is gigantic.+Here's what they don't tell you about that "129 trans prisonersnumber:
  
-**That's exactly what the 59% vs 17% comparison does. It hides the massive difference in group sizes.**+**The MoJ only counts trans prisoners who:** 
 +  * Have had a "case conference" (typically for sentences over 1 year) 
 +  * Have disclosed their trans status 
 +  * Don't have a Gender Recognition Certificate (GRC)
  
-===== Why Per-Capita Distorts the Picture =====+From the MoJ itself:
  
-Much of the time, someone thinks they are clever and will say "it's like you don't understand per-capita." This is different sleight of hand ploy, but related because it still depends on a large disparity between populations (denominators).+> "Prisoners serving long sentences are more likely to be managed as transgender prisoner than those on shorter sentences."
  
-==== The Problem ====+**Why this matters**: Sexual offenses carry longer sentences. So you're only counting the subset of trans prisoners most likely to be sex offenders, then treating that as representative of all trans people.
  
-^ Population ^ Total Size ^ +**From the BBC article**:
-| Trans women population | 48,000 | +
-| Cisgender men population | 29.2 million |+
  
-With such different population sizes:+> "Trans prisoners on shorter sentences—who won't be in the survey—are less likely to be sex offenders."
  
-  A change of just 6 convictions flips the trans women rate dramatically+This is **selection bias**. It's like surveying people at a gym and concluding "most people exercise regularly."
  
-**Trans women:** +==== Trick #3The Completely Fabricated "1,177 per Million" ====
-  * 76 convictions ÷ 48,000 = 15.83 per 10,000 +
-  * 82 convictions ÷ 48,000 17.08 per 10,000 (a 7% change in rate from just 6 more cases)+
  
-**Cisgender men:** +This number **appears in no source document**. Let me show you how it was likely manufactured:
-  * You'd need hundreds of extra convictions to move the needle meaningfully +
-  * 13,234 ÷ 29,177,200 = 4.54 per 10,000 +
-  * You'd need ~13,400+ convictions to get to 4.6 per 10,000+
  
-Yet from this comparison, it looks like trans women will offend 3.5 times more! That sounds really bad!+They took: 76 ÷ 129 = 58.9%
  
-==== Why This Is Misleading ====+Then multiplied by... something? The number is made up.
  
-That 3.5 times more is concerning a fraction of a fraction of a percent of a larger population. It concerns 76 trans women out of 48,000 trans women, which is a fraction of 0.1% of the UK population.+**The actual calculation** (if you wanted to do per-capita, which still has problems):
  
-Some will argue "but per-capita shows over-representation!" That's true; but when comparing populations that differ by a lot (600x or so), small absolute changes produce large percentage swings. Like those six extra convictions mentioned above? They disproportionately inflated the trans women numbers versus the cisgender men.+  * UK trans population: ~48,000-262,000 (estimates vary) 
 +  * Trans women sex offenders in prison: 76 
 +  * Rate: 76 ÷ 48,000 × 1,000,000 = **1,583 per million**
  
-And remember, **the policy question isn't "which group'percentage is higher?" It'"who commits these crimes?"**+Waitthat's even higher! Except it'**still wrong** because: 
 +  * That 76 only counts a snapshot of who'in prison right now 
 +  * It excludes those with GRCs 
 +  * It'subject to the selection bias above 
 +  * **Prison composition ≠ offense rates**
  
-**Answer:** 99.43% cisgender men, 0.57% trans women.+==== Trick #4Misusing the Swedish Study ====
  
-When per-capita is abused (which it absolutely has been throughout history), over-policing of minority groups occurs while the majority of the people actually doing the crime are ignored. Decision-makers believe the data shows them where the real trouble spots/groups are.+Some also cite a 2011 Swedish study (Dhejne et al.) claiming it shows trans women have "male patterns of criminality."
  
-**Note:** One could argue that the per-capita rate does not show over-representation of a group *for committing* the crimes, but *being convicted* for the crimes. These are two different things—but that's a separate issue.+This study: 
 +  Only examined 324 people who had full surgical transition 
 +  Covered 1973-2003 (decades old) 
 +  Found NO difference in the later cohort (1989-2003) 
 +  Has been repeatedly misrepresented
  
-===== The Math in Context =====+**See our full article**: [[debunking-swedish-study|The Swedish Study: What It Actually Says]]
  
-  * Trans women population48,000 +//Short versionIt doesn't support the claims being madeand the author has said so repeatedly.//
-  * Trans women as % of UK population: 0.1% +
-  * Sex offense trans women in prison: 76+
  
-==== Breakdown ====+===== What Counts as a "Sexual Offense" in UK Law? =====
  
-**76 out of 48,000 trans women = 0.158% of trans women population**+Before we analyze the numbers, we need to understand what "sexual offense" actually means in UK law. **It's an extremely broad category.**
  
-Now, what fraction of the TOTAL UK population is this?+==== The Full Scope of UK Sexual Offenses ====
  
-  * UK population: ~59.6 million +Under UK law"sexual offense" includes:
-  * 76 ÷ 59,600,000 = 0.0000012755 = 0.000128% +
-  * **Or1 in 784,000 people in the UK**+
  
-**Once you put it into the right context, it turns out to be not more statistically significant than noise.**+**Serious violent offenses:** 
 +  * Rape and attempted rape 
 +  * Sexual assault and attempted sexual assault 
 +  * Child sexual abuse offenses 
 +  * Indecent assault
  
-===== What IS a Fair Comparison? =====+**Non-violent and non-contact offenses:** 
 +  * Possession of indecent images 
 +  * Distribution of indecent images 
 +  * Making/downloading indecent images 
 +  * Voyeurism 
 +  * Exposure/indecent exposure 
 +  * Outraging public decency
  
-Population comparison is perfectly fine when you are talking about population as a whole! To stay in the same frame of reference, compare trans women to cisgender men in terms of who has the greater proportion of sex offences as a part of their conviction.+**Sex work-related offenses:** 
 +  * Soliciting for prostitution 
 +  * Loitering for prostitution 
 +  * Controlling prostitution 
 +  * Keeping brothel 
 +  * Advertising sexual services
  
-First, total up all those with sex offenses: 13,234 + 76 = 13,310+**Other sexual offenses:** 
 +  * Sexual activity in a public toilet 
 +  * Breach of Sexual Harm Prevention Order 
 +  * Failure to register as sex offender 
 +  * Various consent and age-of-consent related charges
  
-Now find your ratios and put it into a proper chart:+==== Why This Matters ====
  
-{{:sex-offense-convictions-by-group.png?nolink&600|}}+When someone hears "76 trans women sex offenders," most people picture rapists and child abusersBut that category could include:
  
-^ Group ^ Total Sex Offenders ^ Percentage of All Sex Offenders ^ +  * Someone convicted of soliciting for sex work 
-| Cisgender Men | 13,234 | 99.43% | +  * Someone who failed to register an address change as a former offender 
-| Trans Women | 76 | 0.57% |+  * Someone caught with downloaded pornography 
 +  * Someone convicted of public indecency 
 +  * Someone convicted of rape or sexual assault 
 + 
 +**These are NOT equivalent crimes**, yet they're lumped together in the statistics. Without a breakdown, we cannot know the distribution. 
 + 
 +==== The Sex Work Factor ==== 
 + 
 +Trans women, particularly trans women of color, are **disproportionately pushed into survival sex work** due to: 
 +  * Employment discrimination 
 +  * Housing discrimination 
 +  * Family rejection 
 +  * Lack of economic opportunities 
 + 
 +**Research shows**: 
 +  * Trans women are far more likely to engage in sex work than cisgender women 
 +  * Trans women in sex work face higher rates of criminalization 
 +  * Many "sexual offense" convictions are actually sex work-related charges 
 + 
 +This means the "sexual offense" statistics may be **inflated by survival crimes**, not violent offenses. Without detailed breakdowns, we cannot determine how much. 
 + 
 +==== The Emotional Manipulation ==== 
 + 
 +Using the term "sexual offense" without breakdown is **loaded language** designed to invoke fear. It's an appeal to emotion that relies on people assuming all "sex offenders" are rapists. 
 + 
 +**The reality**: The category ranges from rape to soliciting, and treating them as equivalent is intellectually dishonest. 
 + 
 +**What we know**: The MoJ data tells us 76 trans women prisoners had sexual offense convictions. **What we don't know**: The distribution of those offenses across the wide spectrum of UK sexual offense law. 
 + 
 + 
 +===== Why Prison Data Can't Tell You Crime Rates ===== 
 + 
 +**What prison data shows**: Of the prisoners we have right now, here's the breakdown. 
 + 
 +**What it doesn't show**: How likely people are to commit crimes. 
 + 
 +**Why? Because you need:** 
 + 
 +  * Total population size (not just prisoners) 
 +  * Reporting rates 
 +  * Conviction rates   
 +  * Sentencing patterns 
 +  * Who's still in prison vs. who's been released 
 + 
 +**The absurd example**: "75% of maximum security prisoners are violent offenders, therefore 75% of people are violent." 
 + 
 +Obviously wrong—but that's the exact error being made. 
 + 
 +===== The Per-Capita Problem ===== 
 + 
 +When population sizes differ by **600+ times**, per-capita rates become meaningless. 
 + 
 +**Watch what happens**: 
 + 
 +^ Group ^ Convictions ^ Population ^ Rate per 10,000 ^ 
 +| Trans women | 76 | 48,000 | 15.83 | 
 +| Trans women (+6 more) | 82 | 48,000 | 17.08 | 
 +| Cisgender men | 13,234 | 29,177,200 | 4.54 | 
 +| Cisgender men (+6 more) | 13,240 | 29,177,200 | 4.54 | 
 + 
 +**Six additional cases**: 
 +  * Changes trans women rate by **7.9%** 
 +  * Doesn't even round cisgender men rate 
 + 
 +This is why per-capita fails with vastly different population sizes. Small absolute changes create huge percentage swings in the smaller group. 
 + 
 +===== What IS a Fair Comparison? ===== 
 + 
 +Ask the right question: **"Who commits these crimes?"** 
 + 
 +{{ :sex-offense-convictions-by-group.png?600 |}} 
 + 
 +^ Group ^ Sex Offenders ^ Percentage of All Sex Offenders ^ 
 +| Cisgender men | 13,234 | 99.43% | 
 +| Trans women | 76 | 0.57% |
 | **Total** | **13,310** | **100.00%** | | **Total** | **13,310** | **100.00%** |
  
-Now when we ask the question **"Who is responsible for the most sex offenses based on convictions in prison?"** we can look at: +**That'the reality**: 99.43% cisgender men, 0.57% trans women.
-  * The absolute numbers +
-  * The ratio of group A and group B to the category in question +
-  * Determine which one you have more of +
-  * Determine which one is a greater risk (or not)+
  
-==== The Problem with Misused Statistics ====+Now put it in population context: 
 +  * 76 out of ~59.6 million UK population **0.000128%** 
 +  * Or: **1 in 784,000** people
  
-If we took the per-capita rate or the original 59% vs 17% claim, we could end up focusing a lot of resources and police on trans women in an attempt to combat sex offenses in general when they are: +===== The Policy Disaster =====
-  * The smallest population of offenders +
-  * The least compared to the population as a whole+
  
-**Note:** Cisgender women are intentionally left out here due to limited reliable data for this comparisonThere is also an infographic that goes around showing per-capita ratesthis argument applies to that as well, though with different numbers and dataThis has been well covered and debunked already, but in essence, they are using per-capita sleight of hand. If they used absolute numbers and percentages categorized appropriately, it would not be to their advantage.+If you used the manipulated statistics to guide policy, you'd: 
 + 
 +  * Focus resources on 76 people 
 +  * While ignoring 13,234 people 
 +  * Because percentages looked scarier 
 + 
 +This is how over-policing of minorities happens while the majority committing crimes gets ignored. 
 + 
 +**Note**Per-capita doesn't show "propensity to commit crimes." It shows **propensity to be convicted**These are very different thingsbut that's another discussion. 
 + 
 +===== What About Actual Conviction Rates? ===== 
 + 
 +Using **total convicted individuals** (not just prisoners): 
 + 
 +  * **1.27 trans people per million** have sexual offense convictions 
 +  * **222 cisgender men per million** have sexual offense convictions 
 + 
 +Even this comparison has problems (reporting rates, conviction rates), but it's **far more valid** than prison composition data. 
 + 
 +===== What Research Actually Shows ===== 
 + 
 +**Multiple peer-reviewed studies** examining bathroom policies find: 
 + 
 +  * **No increase in sexual assault** in jurisdictions with trans-inclusive bathroom policies 
 +  * **Trans people are victims** of violence at **twice the rate** of cisgender people (UK data) 
 + 
 +The original claim: "There are no recorded cases of a trans woman sexually assaulting a woman in a UK public toilet.
 + 
 +**Prison data doesn't refute this** because: 
 +  * Doesn't specify location of offenses 
 +  * Doesn't distinguish offense types 
 +  * Can't tell us about bathrooms specifically
  
 ===== Summary ===== ===== Summary =====
  
-**"There are lies, damned lies, and statistics"**+//"There are lies, damned lies, and statistics."// 
 + 
 +The claims rest on: 
 + 
 +  * **Comparing percentages of vastly different sized groups** (76 vs 13,234) 
 +  * **Selection bias** (only counting long-sentence prisoners) 
 +  * **Fabricated statistics** ("1,177 per million" appears nowhere) 
 +  * **Confusing prison composition with crime rates** (completely different calculations) 
 +  * **Misusing per-capita** (doesn't work with 600x population differences) 
 + 
 +**The reality**: 
 +  * 99.43% of sexual offense prisoners are cisgender men 
 +  * 0.57% are trans women 
 +  * That's 1 in 784,000 people in the UK 
 +  * Research shows no safety concerns with trans-inclusive policies 
 + 
 +When statistics are presented without proper context or with misleading comparisons between vastly different group sizes, they distort reality. 
 + 
 +===== Sources ===== 
 + 
 +  * Fair Play for Women submission to Parliament (2020) 
 +  * BBC Reality Check: "How many transgender inmates are there?" (2018) 
 +  * UK Ministry of Justice FOI data (2019-2020) 
 +  * Stop Hate UK: Transgender hate crime statistics 
 +  * American Academy of Pediatrics: Bathroom policy studies 
 +  * Springer: Safety and privacy research
  
-When statistics are presented without proper context or with misleading comparisons between vastly different group sizes, they distort reality. The fair way to present data is:+----
  
-  * Use absolute numbers when the populations differ significantly +//This article aims to promote evidence-based policy discussion by clarifying common statistical manipulation. Good-faith questions about data interpretation are welcomed; weaponizing statistics to promote fear serves no one.//
-  * Use ratios/percentages of the total within the category being measured +
-  * Always contextualize within the total population affected +
-  * Ask: "What is the actual policy question?" and ensure the statistics answer that question, not a misleading version of it+
  
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