Differences

This shows you the differences between two versions of the page.

--- common-myths-debunked [2025/12/21 21:03] – [What This Actually Shows] valah
+++ common-myths-debunked [2025/12/25 14:57] (current) – valah
@@ Line 1: / Line 1: @@
-====== Statistical Sleight of Hand: How 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 ^
 | 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**
-**Note:** Keep in mind that "sex offence" in the UK is a rather broad bucket, which includes various charges surrounding being paid for, and participating in, sex work. Trans women, on average, are more likely to take sex work as a means of survival. So there is an element of //appeal to emotion// and or //loaded language// when making the shocking or damning sounding claim of "sex offense conviction(s)."
+  * Classroom A: 129 students, 76 like chocolate = 58.9%
+  * Classroom B: 78,781 students, 13,234 like chocolate = 16.8%
-===== The Classroom Analogy =====
+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.
-Imagine two classrooms:
+==== Trick #2: Ignoring Who Gets Counted ====
-  * **Classroom A:** 129 students total, 76 like chocolate = 58.9%
+Here's what they don't tell you about that "129 trans prisoners" number:
-  * **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.
+**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)
-**That's exactly what the 59% vs 17% comparison does. It hides the massive difference in group sizes.**
+From the MoJ itself:
-===== Why Per-Capita Distorts the Picture =====
+> "Prisoners serving long sentences are more likely to be managed as a transgender prisoner than those on shorter sentences."
-Much of the time, someone thinks they are clever and will say "it's like you don't understand per-capita." This is a different sleight of hand ploy, but related because it still depends on a large disparity between populations (denominators).
+**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.
-==== The Problem ====
+**From the BBC article**:
-^ Population ^ Total Size ^
+> "Trans prisoners on shorter sentences—who won't be in the survey—are less likely to be sex offenders."
-| Trans women population | 48,000 |
-| Cisgender men population | 29.2 million |
-With such different population sizes:
+This is **selection bias**. It's like surveying people at a gym and concluding "most people exercise regularly."
-  * A change of just 6 convictions flips the trans women rate dramatically
+==== Trick #3: The Completely Fabricated "1,177 per Million" ====
-**Trans women:**
+This number **appears in no source document**. Let me show you how it was likely manufactured:
-  * 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:**
+They took: 76 ÷ 129 = 58.9%
-  * 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!
+Then multiplied by... something? The number is made up.
-==== Why This Is Misleading ====
+**The actual calculation** (if you wanted to do per-capita, which still has problems):
-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.
+  * 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**
-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.
+Wait, that's even higher! Except it's **still wrong** because:
+  * That 76 only counts a snapshot of who's in prison right now
+  * It excludes those with GRCs
+  * It's subject to the selection bias above
+  * **Prison composition ≠ offense rates**
-And remember, **the policy question isn't "which group's percentage is higher?" It's "who commits these crimes?"**
+==== Trick #4: Misusing the Swedish Study ====
-**Answer:** 99.43% cisgender men, 0.57% trans women.
+Some also cite a 2011 Swedish study (Dhejne et al.) claiming it shows trans women have "male patterns of criminality."
-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.
+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
-**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.
+**See our full article**: [[debunking-swedish-study|The Swedish Study: What It Actually Says]]
-===== The Math in Context =====
+//Short version: It doesn't support the claims being made, and the author has said so repeatedly.//
-  * Trans women population: 48,000
+===== What Counts as a "Sexual Offense" in UK Law? =====
-  * Trans women as % of UK population: 0.1%
-  * Sex offense trans women in prison: 76
-==== Breakdown ====
+Before we analyze the numbers, we need to understand what "sexual offense" actually means in UK law. **It's an extremely broad category.**
-**76 out of 48,000 trans women = 0.158% of trans women population**
+==== The Full Scope of UK Sexual Offenses ====
-Now, what fraction of the TOTAL UK population is this?
+Under UK law, "sexual offense" includes:
-  * UK population: ~59.6 million
+**Serious violent offenses:**
-  * 76 ÷ 59,600,000 = 0.0000012755 = 0.000128%
+  * Rape and attempted rape
-  * **Or: 1 in 784,000 people in the UK**
+  * Sexual assault and attempted sexual assault
+  * Child sexual abuse offenses
+  * Indecent assault
-**Once you put it into the right context, it turns out to be not more statistically significant than noise.**
+**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
-===== What IS a Fair Comparison? =====
+**Sex work-related offenses:**
+  * Soliciting for prostitution
+  * Loitering for prostitution
+  * Controlling prostitution
+  * Keeping a brothel
+  * Advertising sexual services
-Population comparison is perfectly fine when you are talking about a 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.
+**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
-First, total up all those with sex offenses: 13,234 + 76 = 13,310
+==== Why This Matters ====
-Now find your ratios and put it into a proper chart:
+When someone hears "76 trans women sex offenders," most people picture rapists and child abusers. But that category could include:
-{{:sex-offense-convictions-by-group.png?nolink&600|}}
+  * Someone convicted of soliciting for sex work
+  * Someone who failed to register an address change as a former offender
+  * Someone caught with downloaded pornography
+  * Someone convicted of public indecency
+  * Someone convicted of rape or sexual assault
-^ Group ^ Total Sex Offenders ^ Percentage of All Sex Offenders ^
+**These are NOT equivalent crimes**, yet they're lumped together in the statistics. Without a breakdown, we cannot know the distribution.
-| Cisgender Men | 13,234 | 99.43% |
-| Trans Women | 76 | 0.57% |
+==== 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%** |
-Now when we ask the question **"Who is responsible for the most sex offenses based on convictions in prison?"** we can look at:
+**That's 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 comparison. There is also an infographic that goes around showing per-capita rates—this argument applies to that as well, though with different numbers and data. This 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 things—but 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 =====
-**"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

Trace: • debunking-tw-offend-rate • common-myths-debunked

Differences

Search

Navigation

Print/export

Tools

QR Code