Disinformation Report: July 16-31

How Anti-Trans Attacks Are Landing Across TFA’s Priority States — and How Campaigns Should Answer

For the first time in this tracking, the loudest attack in any priority state targeted a candidate: the national pile-on against Ashley Webb, the trans and intersex contender for Maine’s replacement Senate nomination — Breitbart, the New York Post, and an explicit deadnaming post from Andy Ngo, 6M+ engagements inside a live nomination contest. Minnesota ran second on a manufactured story about “transgender dolls in schools” that is false in every load-bearing detail, and drew a real federal investigation anyway. This briefing maps how the period’s attacks landed across the thirteen states TFA is tracking: who drove each story, who it reached, and which counter-messages test best now.

July 16 – July 31, 2026

Data: Trans Rhetoric Social Media Dashboard

79K+ channels | 20 platforms | 1M+ posts

13 priority states | 629 state-tagged posts | 11.2M engagements | c4 / Organize Action

Topline Finding

The state map re-localized this period, and it did so in the worst way available: around a candidate. Maine carried the highest priority-state reach this tracking has recorded, nearly all of it a national delegitimization campaign against Ashley Webb, the trans and intersex contender to replace Graham Platner as the Democratic Senate nominee — Breitbart’s headline about her body (2.2M), a New York Post debate clip, Breaking911, and Andy Ngo publishing what he called her “real identity.” Webb did not qualify for the July 25 replacement convention that nominated Troy Jackson, but the attacks did not depend on her chances; they set the template for the next trans candidate who files anywhere. Minnesota ran second on a false manufactured story — “transgender dolls” in schools, attached to Gov. Walz one week before the 8/11 primary — and Michigan’s story was the federal Education Department threatening a district’s funding days before its own primary. The rest of the field was quiet on state terrain while the national conversation (the UCF bodycam clip, Sophie Cunningham, the Correspondents’ Dinner) ran elsewhere. Quiet is not safe: the three loudest state stories this period were a candidate attack, a fabrication, and a federal enforcement lever — none of which requires a legislature to be in session.

Source: Trans Rhetoric Dashboard | issue-location layer, off-topic virality removed | reach labeled for states above 100k

Maine dominates the map this period — the Webb pile-on gave it more reach than every other priority state combined. Florida (the UCF bodycam story) and Washington (the Storm co-owner incident) led off-list; the priority-state signal is candidate-shaped, not legislature-shaped.

Source: Trans Rhetoric Dashboard | issue-location layer, off-topic virality removed

Reach is concentrated to an extreme this period: Maine towers over the field, Minnesota and Texas follow, and most states sit near zero. Concentration means the attacks are choosing their targets — not spraying.

Key Findings

• A trans candidate drew the biggest priority-state attack this tracking has recorded. The pile-on against Ashley Webb in Maine — Breitbart (2.2M), the New York Post, Breaking911, and Andy Ngo’s explicit deadnaming post — made Maine worth more reach than every other priority state combined. Deadnaming-as-opposition-research will recur wherever a trans candidate or staffer files; the standing protocol should exist before the next one does.

• The attacks outlived the candidacy. Webb failed to qualify for the July 25 replacement convention (Troy Jackson is the nominee against Sen. Collins), but attack posts kept circulating after she was out. The format does not need a viable target — it needs a trans person near a ballot.

• Minnesota’s second-place reach is a fabrication. The “Walz-backed transgender dolls in schools” story is false in every load-bearing detail — the real item is a University of Minnesota Medical School therapeutic tool for licensed clinicians, with no state program, no Walz role, and no classroom use. It still drew a federal Education Department investigation and sits one week ahead of the 8/11 primary.

• The federal-enforcement lever reached two more primary states. The US Education Department threatened a Michigan district’s funding over trans policies days before the 8/4 primary; America First Legal sued a North Carolina district July 31; the Kansas City district got a demand letter. Institutional-litigation attacks don’t need a legislature — or a viral moment — and they generate local news for months.

• The girls’-sports lane is being organized in-state, on a schedule. Wisconsin’s one big item was a New Richmond school-board clip (164K) — and a Riley Gaines rally in the same town is scheduled for Aug 4, a week before the primary. The national Cunningham story gives this lane fresh cover everywhere.

• The anti-trans audience re-masculinized with the sports mix. Anti-trans priority-state content reached a 64%-male, Gen-X-heavy audience this period — last cycle’s gender-balanced read is gone with the entertainment content that produced it. Audience composition tracks the content mix; re-check it each cycle.

• On sports terrain, the opposition’s frames outtest ours — the winning counter goes around them. In this period’s MaxDiff (fielded on the Cunningham/WNBA narrative), opposition frames hold the top two slots. The best counter-material doesn’t argue eligibility: the kids-off-limits message built on the Storm bleacher incident wins 82% overall and 91% with Independents, and “let leagues decide, not politicians” is the strongest single ingredient (+14).

• Direct defense and statistics actively hurt on this terrain. Defending trans athletes directly (−15.1), dignity/inclusion language (−15.1), and the small-numbers fact (−9.1) all reduce a message’s win rate. What campaigns reach for by instinct is what tests worst; the tested alternative is on the Messaging pages.

• Texas cooled on trans terrain. The Paxton–Talarico fight stayed loud, but this window’s attacks ran on authenticity (the “fake Ford commercial” line), not trans issues, and last period’s near-even stance split did not recur. The lane is still open — the “Low T Talarico” video tracking request stands.

The Battleground at a Glance

Two layers drive this briefing. The issue-location layer tags which state each post is about; the account-location layer tags where the messenger is based. A post can be about a state without originating there (a national account attacking Roy Cooper counts toward North Carolina), so the reach figures below measure attention on a state, not local activity alone. Off-topic virality that keyword-matched a state (foreign-language tabloid items, unrelated news) has been removed by hand.

State	Primary	Posts	Reach	vs last	Anti / Pro	Top messenger
Maine	6/9/26	255	6.6M	▲ 828%	139K / 440K	Breitbart News
Minnesota	8/11/26	146	1.3M	▲ 13x	525K / 10K	Eric Daugherty
Texas	TBD	64	1.2M	▼ 11%	334K / 62K	Mike Lee
Iowa	TBD	20	709K	▲ 429x	0 / 2K	Libs of TikTok
Michigan	8/4/26	57	603K	▲ 411%	145K / 216K	Shannon Watts
Wisconsin	8/11/26	31	230K	▼ 47%	194K / 10K	Libs of TikTok
New Hampshire	9/8/26	37	163K	▼ 11%	31K / 667	Gillian Branstetter
North Carolina	3/3/26	10	159K	▲ 13x	140K / 10K	America First Legal
Georgia	5/19/26	15	130K	▼ 63%	72K / 16K	NewsWire
Arizona	8/4/26	13	30K	▼ 55%	20K / 2K	Lila Rose
Nevada	6/9/26	1	23K	≈	0 / 0	Shipwreckedcre w
Pennsylvania	5/19/26	13	18K	▼ 74%	0 / 368	The Advocate
Kansas	TBD	14	15K	▼ 81%	28 / 2K	Headlines Plus

“vs last” compares reach with the previous reporting period (≈ means within ±10%). A rising state deserves attention before its number is large.

Source: Trans Rhetoric Dashboard | stance classifier; "neutral" includes hostile-leaning news coverage

Tone is a directional read from the stance classifier; “neutral” absorbs a large amount of hostile-leaning coverage, so anti-trans shares are conservative — Maine is the extreme case this period: most of the Webb pile-on is stance-coded neutral, so the state’s hostile share drastically understates what the reach actually was. Iowa’s bar has the same problem (the Libs of TikTok villain story codes neutral). Read the stance chart alongside the notes, not instead of them.

Who’s Driving the Conversation

Right-Leaning Drivers

Breitbart News — 2.2M on a single Webb attack post

The single largest priority-state attack post of the period — a headline about Ashley Webb’s body, published while the Maine replacement contest was live. National outlet, candidate target, state consequence: the exact shape the standing protocol needs to anticipate.

Andy Ngo — 29 posts in the window

Published what he called Webb’s “real identity” — deadnaming as opposition research, presented as journalism. High volume across the period on trans-crime framing generally; the Webb post is the one with an electoral target.

Eric Daugherty — 4.2M engagements, 26 posts

Drove both of the period’s manufactured-or-distorted state stories: the Minnesota “dolls” fabrication (682K across two posts) and the NDAA amendment revolt coverage. A wire-service format — “🚨 JUST IN” — that moves aggregator content toward official audiences fast.

Libs of TikTok — 9.1M engagements, 62 posts

The tip-line again: the Iowa villain story (661K), the Wisconsin school-board clip (164K), and a stream of individual-target items that larger outlets pick up. Still the point in the chain where a state story can be anticipated before it scales.

Left-Leaning Drivers

Dylan Mulvaney — 6.1M engagements, one post

Her July 26 response to the Correspondents’ Dinner joke — composed, first-person, closing on an ask — out-reached every other left-leaning account’s entire two weeks and anchored the period’s only left-led day. Not a state story, but the template state campaigns should study: the target answering in her own voice beat every institutional response.

Brianna Turner — 427K, athlete-to-athlete

The Las Vegas Aces player answered the Cunningham cluster directly, amplifying Lynx coach Cheryl Reeve’s “exclusion is never the answer.” The only counter-format that traveled inside the sports story — and it maps onto any state with a team or a Division I program.

Gillian Branstetter — 85K, the argument itself

The ACLU strategist’s post clarifying what trans advocates actually argued at the Supreme Court was New Hampshire’s largest item — evidence that a clean corrective can out-travel local attack content in a small state.

How the Attacks Travel — Originators vs. Amplifiers

Two different jobs create anti-trans reach. A small set of accounts originate stories — surfacing a local incident that then spreads; a larger set amplify, putting the most eyeballs on stories someone else started. The two call for different campaign responses: pre-empt originators, rapid-respond to amplifiers.

Top originators (seed stories that travel): Fox News (31.3M, 18 seed stories); New York Post (15.9M, 2 seed stories); DiscussingFilm (6.3M, 3 seed stories); PBD Podcast (5.6M, 1 seed story); Leading Report (5.3M, 5 seed stories).

Top amplifiers (most reach on others’ stories): Fox News (all accounts) (10.5M, 24 reposts); The Associated Press (2.9M, 1 repost); Outnumbered Fox News (1.5M, 1 repost).

Who These Attacks Reach

The dashboard has no engager-level data, so audience is modeled — inferred from the demographics of the accounts that produce and amplify content, weighted by engagement, under a homophily assumption. It blends US Census surname data, Social Security first-name records, each platform’s known user base, and where accounts are based. For the roughly 82% of anti-trans reach carried by accounts with a real name or seed match this period, this is a genuine read; the rest falls back to a national baseline. Treat it as directional, not measured — but the split between the two sides is stark enough to act on.

Audience of…	Gender	Top age cohorts	Race (modeled)	Evidence	Conf.
Anti-trans attacks	64% male / 36% female	Gen X 30% · Millennial 28% · Boomer 21%	White 70% · Hispanic 17% · Black 8%	82%	0.67
Pro-trans content	55% female / 45% male	Millennial 38% · Gen X 25% · Gen Z 19%	White 78% · Black 11% · Hispanic 6%	45%	0.56
All state content	54% male / 46% female	Millennial 34% · Gen X 26% · Gen Z 22%	White 75% · Hispanic 9% · Black 9%	44%	0.50

The pendulum swung back: anti-trans state content reached a 64%-male, Gen-X-heavy audience this period — last cycle’s gender-balanced read is gone along with the entertainment content that produced it. The candidate-attack and sports mix pulled the audience profile back toward the older-male core, while pro-trans content reached its usual majority-female millennial audience — the two sides of this fight are, again, largely talking to different rooms. One measurement note cuts in this table’s favor: the evidence share for the anti-trans slice is unusually high (82%) and confidence is up (0.67), because so much of the reach ran through large named outlets rather than anonymous accounts — this period’s anti-trans row is the most trustworthy this model has produced. “Evidence” is the share of reach from accounts with a real name/seed match rather than a national-average fallback; “Conf.” is the mean modeled confidence. The racial estimate is the weakest layer and should be read most loosely.

Case Studies

Case Study 1: Maine — Deadnaming as Opposition Research

What happened. After Graham Platner withdrew from the Senate race in early July, the Maine Democratic Party set a July 25 delegate convention to choose his replacement against Sen. Susan Collins. Ashley Webb, a trans and intersex activist, declared for the nomination — and drew a national attack wave within days of her first debate: Breitbart published a headline about her body (2.2M — the largest priority-state attack post this tracking has recorded), the New York Post ran a debate clip as a mockery item, Breaking911 circulated an interview excerpt, and Andy Ngo published what he called her “real identity,” with her birth name and birthdate. Webb did not meet the party’s 500-signature qualification threshold and was off the candidate list by July 22; the convention nominated former state Senate president Troy Jackson. The attack posts kept circulating after she was out.

Why it matters. This is the first time in this tracking that the largest state story was an attack on a trans candidate, and the mechanics are portable: none of it engaged her platform, all of it was aimed at the fact of her body and her name, and it scaled through national outlets that have no Maine audience. The format does not require a viable candidacy — a longshot contender drew eight-figure aggregate reach — which means every trans candidate and senior staffer in the country is a potential anchor for the same wave.

Takeaway. The protocol has to exist before the person files. Campaigns with a trans candidate or staffer need a standing posture: what gets answered (facts, records, qualifications), what gets ignored (anatomy, birth names — engaging validates the frame), and who else carries the response so the target isn’t answering alone. The Mulvaney response this period (see the c3 briefing) is the working model: first-person, composed, closing on an ask — and it was the only format that beat the attack machine on any day of this window.

Case Study 2: Minnesota — The Manufactured Program

What happened. Right-wing accounts claimed a “Walz-backed program” would put “transgender dolls with removable, interchangeable genitalia” into Minnesota schools for children as young as four (Eric Daugherty, 682K across two posts; Rep. Nancy Mace, 131K; Fox’s Outnumbered, 1.5M on Facebook). The claim is false in every load-bearing detail. The real item — MyGender Dolls — is a University of Minnesota Medical School project: an anatomically flexible therapeutic tool for licensed clinicians working with gender-diverse children, with required training, no launch date, no classroom use, no state funding, and no connection to the governor’s office (Walz’s link is a 2023 award from the institute — an award, not program backing). The state education department called the classroom claim “patently false.” The distortion still worked: by July 30 the US Education Department had opened an investigation of Minnesota’s education agency — over a program that agency neither runs nor funds.

Why it matters. This is the manufactured-local-program format at its most complete: a real object (the dolls exist), a false chain of attribution (university → state → governor → classrooms), a named Democratic target one week before his state’s primary, and a federal enforcement action that launders the fabrication into legitimate-sounding news. The shape survives into a thirty-second ad even after the fact-checks land.

Takeaway. The accurate receipt is the counter: not “this is a smear” but the specific chain — a university clinical tool, mandatory professional training, zero state dollars, zero classrooms, and an education department investigating a program it doesn’t run. Campaigns in Minnesota need that one-pager now, before the ad, because the correction is only useful while it’s faster than the attack.

Case Study 3: The Bleachers — When the Sports Fight Reached the Stands

What happened. Indiana Fever guard Sophie Cunningham’s July 21 ESPN profile — opposing trans women in women’s sports — became a two-week national story (see the c3 briefing). It reached priority-state terrain on July 28 in Seattle: Storm minority co-owner Celeste Keaton confronted two teenage fans wearing anti-trans-inclusion brand shirts and holding pro-Cunningham signs courtside. The WNBA fined Keaton and suspended her from five home games; the Storm apologized; Fox and Outkick ran the teens’ interview as an exclusive. Right-wing accounts turned the confrontation into the period’s freshest victim story — an adult berating “teenage girls” — and a Riley Gaines rally is now scheduled in New Richmond, Wisconsin for Aug 4.

Why it matters. The bleacher incident, not the eligibility argument, is what this period’s message testing was fielded on — and it shows why the incident is dangerous: adults-versus-kids is the one frame in this fight that moves everyone, and this time it ran against our side. But the same testing shows the frame is symmetric. The single best-testing message of the period (82% overall, 91% with Independents) turns the bleacher incident into a kids-off-limits principle that covers the teens in the stands and the trans kids the debate is about — conceding nothing on eligibility while refusing the us-versus-them premise.

Takeaway. Don’t defend the confrontation and don’t relitigate eligibility. The tested answer leads empathetic, extends kids-off-limits to every kid in the story, and hands rule-making to leagues (“let leagues decide, not politicians” — the strongest ingredient, +14). Athlete validators carry it best: Brianna Turner amplifying Cheryl Reeve’s “exclusion is never the answer” was the only counter-content that traveled inside the sports cluster.

Attack Formats to Watch

• Deadnaming as opposition research. Maine’s evolution of the candidate attack: the target’s body and birth name presented as investigative findings, scaled through national outlets. It needs no viable candidacy and no policy hook. Every trans candidate and senior staffer is a potential anchor; the protocol (answer the record, never the anatomy, and never alone) should pre-exist the filing.

• The manufactured local program. Minnesota’s dolls story: a real object, a false attribution chain, a named Democratic executive, and a federal investigation that launders the fabrication. The counter is the accurate receipt, prepared before the ad — the specific chain of what the program is and isn’t.

• The federal-enforcement lever. Education Department funding threats (Michigan), demand letters (Kansas City), and impact litigation (America First Legal v. Cabarrus County, NC) generate months of local news without a viral moment or a legislature. School boards in Senate-race states are the target surface.

• The bleacher confrontation. Seattle proved every arena interaction is now potential content, and adults-versus-kids is the frame that moves everyone. Assume cameras; the kids-off-limits answer has to cover every kid in the story or it reads as partisan.

• The individual-villain story, still running. Iowa’s TikToker item (661K) and the UCF bodycam clip nationally: a private person’s worst moment as a state-tagged attack. No correction path exists; the discipline is recognition (clip age, context) and refusal to relitigate the person.

Which Counter-Messages Land — Message Testing (MaxDiff)

This period’s message testing was fielded August 1 on the period’s dominant narrative — the women’s-sports fight reignited by Sophie Cunningham’s ESPN comments and the Seattle Storm bleacher incident. A synthetic MaxDiff panel showed candidate messages in head-to-head pairs to voter archetypes weighted to the electorate; “selection rate” is the share of match-ups a message or ingredient wins. The July healthcare playbook does not carry over to sports terrain — and the most important result is a warning, not a recipe.

1. By frame — re-weighted to the audience you reach

The frame-level view, re-weighted to the gender and age of the audience the attacks reach (the 64%-male, Gen-X-heavy skew from the previous section). ▲/▼ mark frames that over- or under-perform with that audience versus a generic likely-voter panel. Opposition frames were tested with equal craft and are labeled.

Frame	Win %	Read
Opposition: silent majority	69.5%	Top frame; #1 with likely voters too
Opposition: even Democrats agree	68.0%	Under-indexes with reached audience ▼
Overreach / governance	65.8%	Under-indexes with reached audience ▼
Family freedom	65.0%	Best-testing counter-frame
Opposition: common sense	59.7%
Science / evidence	58.2%
Opposition: protect girls	55.6%	Over-indexes with reached audience ▲
Cruelty has limits	52.2%	Over-indexes with reached audience ▲
Fairness / inclusion	50.6%	Under-indexes with reached audience ▼
Individual assessment	41.6%	Over-indexes with reached audience ▲
Discrimination	36.2%	Under-indexes with reached audience ▼
Opposition: zero-sum fairness	32.7%	Over-indexes with reached audience ▲
Distraction / priorities	32.3%
Electoral warning	20.4%	Weakest-testing

Read the top of this table honestly: on sports terrain, the opposition’s frames outtest every counter-frame we have. “Silent majority” (69.5%) and “even Democrats agree” (68.0%) lead the board; our best counters — family freedom (65.0%) and, with the reached audience specifically, cruelty-has-limits — compete but do not win the frame war head-on. The implication runs through the rest of this section: the winning counter-messages don’t fight on the eligibility frame at all. They change what the argument is about.

2. The best-testing messages, verbatim

All four leaders share a construction: empathetic register, kids-off-limits or family ground, no direct eligibility defense (Independent selection rate shown alongside the overall).

Message (excerpt)	Overall	Ind.	Frame · register
“A grown adult screamed at two teenage girls at a basketball game because of a political fight. Whatever you believe about this issue, if it has adults berating somebody’s kids in the bleachers, the fight itself has gone somewhere sick. Kids are off-limits. All of them — the ones in the stands and the ones this debate is actually about.”	82.1%	90.6%	cruelty-has-limits · empathetic
“I’m a parent. I don’t want politicians deciding who makes my kid’s team, I don’t want strangers screaming at children in the bleachers, and I don’t want any kid — including a trans kid — dreading school because adults turned her into a talking point. Protect all our kids. That’s the whole position.”	69.5%	75.0%	family freedom · empathetic
“You can care about fair competition and still refuse to turn a teenager’s life into a national spectacle. Most Americans hold both of those thoughts at once. The people who can’t are the ones with campaign ads to sell — and they need you to believe your neighbors are the enemy.”	68.6%	75.5%	cruelty-has-limits · empathetic
“This month, one player got a mob for saying what she thinks, and a teenager got screamed at by an adult for cheering. That’s where this fight has taken us: everybody’s somebody’s target. Americans are allowed to disagree about sports rules without trying to destroy each other over it.”	68.0%	69.8%	cruelty-has-limits · empathetic

The top message — built directly on the bleacher incident — wins 82% overall and 91% with Independents. Note what it does: it concedes nothing on eligibility, extends kids-off-limits to the trans kids the debate is about, and indicts the fight itself rather than either side’s position. The decency claim does the work the eligibility argument can’t.

3. What makes a message work

Holding the topic constant, three variables move a message more than its frame label does: register, the antagonist it names, and the argument ingredients it carries.

Register — lead empathetic; outrage collapsed on this terrain:

Register	Avg win %
Empathetic	61.3%	Best-testing register
Practical	57.0%
Measured	51.0%
Outrage	28.2%
Aspirational	12.9%	Weakest (one message tested)

Antagonist — “politicians in Washington” again; naming Trump tests worst:

Villain named	Avg win %
“Politicians in Washington”	60.5%	Best-testing antagonist
“The government”	54.4%
No antagonist named	49.7%
“Republican politicians”	43.4%
“The administration”	40.1%
Naming Trump	39.6%	Weakest

Argument ingredients — the lift each adds:

Ingredient in the message	Lift
Let leagues decide (“not politicians”)	+14.0	strongest lift
Cruelty theme (“the fight has gone somewhere sick”)	+12.3
Government-overreach label	+11.4
Acknowledging fairness-to-women concerns	+9.3
Kids-bullying theme	+7.7
Naming specific people	−1.6	— slightly hurts
Electoral consequence	−4.7	— slightly hurts
Distraction-from-economy pivot	−7.6	— hurts
Small-numbers fact (“less than 1%”)	−9.1	— hurts
Dignity / inclusion language	−15.1	— hurts
Defending trans athletes directly	−15.1	— hurts

“Let leagues decide” is the strongest single ingredient (+14.0) — handing rule-making to sports bodies lets voters exit the political fight without picking a side. The cruelty theme (+12.3), the overreach label (+11.4), and — notably — acknowledging fairness-to-women concerns (+9.3) all add lift. The bottom of the table is the sharper finding: defending trans athletes directly (−15.1), dignity/inclusion language (−15.1), and the small-numbers statistic (−9.1) all actively hurt — the three moves advocacy communications reaches for first. The economy-distraction pivot also hurts (−7.6): on a story about kids in bleachers, changing the subject reads as evasion.

4. The bottom line for messaging

Build the counter as an empathetic, kids-off-limits story that acknowledges the fairness concern and hands the rules to leagues: every kid in this story deserves to not be a national target, most Americans can hold fairness and decency at once, and eligibility is for leagues and governing bodies — not politicians. Keep Trump’s name out of the villain slot, keep the statistics out entirely, and put it in an athlete’s mouth where possible. Modeled signal — pair with live polling before ad spend.

Looking Ahead — The Primary Calendar

August primaries land inside the attack window (MI + AZ 8/4, MN + WI 8/11). Michigan votes with a federal funding threat against one of its districts days old; Minnesota votes one week after the dolls fabrication attached to the governor’s office; Wisconsin votes a week after the scheduled Riley Gaines rally in New Richmond. Expect the sports and schools creative to sharpen through both weeks.

[DEVELOPING] The Storm co-owner fallout is three days old. The fine, the suspension, the apology, and the teens’ Fox/Outkick interview all landed July 28–31 — most of the story’s engagement belongs to the next period. Watch for it to migrate into paid creative as the cleanest adults-versus-kids victim story the right has had in months.

Maine’s general is now set: Jackson vs. Collins, with the Webb portfolio on the shelf. The attack machinery built against Webb — the outlets, the framings, the audience — does not retire with her candidacy. Watch for it to be re-aimed at trans staff, endorsers, or down-ballot candidates in Maine and elsewhere.

Federal-enforcement docket grows through the fall. The Minnesota ED investigation, the Michigan/Maryland funding threats, the Kansas City demand letter, and AFL v. Cabarrus County will each produce recurring local news on school terrain through the semester — implementation stories are attack surfaces or openings depending on who frames them first.

Ciscomani paid-rotation watch (standing request). No new girls’-sports post from his account this window; the watchlist flags every new one. The open question from the July 8 ask remains whether the earlier creative enters paid rotation — the next c4 will report whatever the ad-library check finds.

Strategic Recommendations

COUNTER	PIVOT AWAY	LEAN INTO
• The trans-candidate protocol (Maine): a standing posture for deadnaming-as-oppo before the next filing — answer the record, never the anatomy; surrogates carry the response so the target isn’t answering alone. • The manufactured-program receipt (Minnesota): the one-page accurate chain — university clinical tool, required training, no state dollars, no classrooms — pre-drafted before it becomes an ad.	• Direct eligibility defense, dignity/inclusion language, and the small-numbers statistic — all three actively reduce win rates on sports terrain (−15.1 / −15.1 / −9.1). • The economy-distraction pivot (−7.6) and Trump-naming (weakest antagonist) — changing the subject and personalizing the villain both test as evasion here.	• The kids-off-limits frame, athlete-carried — 82% overall, 91% with Independents, built on the bleacher incident; Turner/Reeve proved the athlete-validator lane travels. • “Let leagues decide, not politicians” (+14.0, the strongest ingredient) plus acknowledging the fairness concern (+9.3) — the exit ramp that lets persuadables leave the fight without picking a side.

The bottom line. The state map stopped being an abstraction this period: the biggest attack in the field was aimed at a candidate’s body, the second-biggest was a fabrication attached to a governor a week before his primary, and the federal government supplied the enforcement lever in three more states. None of that machinery requires the attacks to be true, and none of it retires when a candidacy ends. The message testing is equally blunt: on sports terrain the opposition’s frames win head-on, the instinctive defenses actively hurt, and the one message that beats everything extends kids-off-limits to every kid in the story and hands the rules to leagues. Build the two protocols — the trans-candidate posture and the manufactured-program receipt — before the August primaries put them to use.

Limitations

Geography is measured from two dashboard layers: issue-location (which state a post is about; ~10% of posts carry a state tag) and account-location (where a channel is based; ~2% of channels). A post can be about a state without originating there, so state reach measures attention, not local activity. Off-topic virality that keyword-matched a state (foreign-language tabloid items, unrelated news) was removed by hand. Stance (anti/pro/neutral) is a directional classifier read; “neutral” absorbs much hostile-leaning news, so anti-trans shares are conservative.

The audience read is modeled, not observed: the dashboard has no engager-level data, so audience is inferred from the demographics of the accounts producing and amplifying content, engagement-weighted, under a homophily assumption (producer ≠ audience is the foundational caveat). It blends Census surname data, SSA first-name records, platform user base, and account location; the “evidence” column reports the share of reach with a real name/seed match versus a national fallback. The racial estimate is the weakest layer (only ~2% of channels have a state) and is hedged hardest. The originator/amplifier read is modeled from near-duplicate text clustering plus native amplifier edges captured for ~36% of posts. The MaxDif frame fit is modeled × modeled — a synthetic panel re-weighted to a modeled audience — a directional signal, not a poll. Engagement is not persuasion.

Methodology

Data source. Trans Rhetoric Social Media Dashboard, built for TFA on the Junkipedia social listening API — 79,000+ channels across 20 platforms, 1,000,000+ posts spanning December 2023 to present, collected on 90+ keywords (topic terms, framing terms, and named trans public figures). Period: July 16 – July 31, 2026. Priority states are drawn from Adrienne’s “TFA priority states-races 5.18.26” sheet, plus Iowa (Jun 9 request) and Texas/Talarico. Per-state signal uses two geolocation layers — issue-location (which state a post concerns) and account-location (where a channel is based) — filtered to trans-relevant posts carrying engagement, with a manual audit of the high-engagement tail to remove off-topic keyword matches.

Message Testing (MaxDiff)

The messaging results come from a MaxDiff (maximum-difference scaling) exercise fielded August 1 on the period’s governing narrative — the women’s-sports fight reignited by Sophie Cunningham’s ESPN comments and the Seattle Storm bleacher incident. The instrument is a set of 25 candidate messages written to vary systematically along four dimensions — frame (kids-off-limits, family freedom, cruelty-has-limits, let-leagues-decide, overreach/governance, fairness/inclusion, science/evidence, individual assessment, distraction, discrimination, electoral warning, and a set of opposition frames), the antagonist named (“politicians in Washington,” “the government,” “Republican politicians,” “the administration,” Trump, or none), rhetorical register (empathetic, practical, measured, outrage, aspirational), and eleven binary argument-elements (e.g. let-leagues-decide, the cruelty theme, the small-numbers fact). Opposition messages are included and written with equal craft, not as strawmen — this period they anchor the top of the frame table, which is itself a finding.

The instrument is fielded against a panel of 21 voter archetypes weighted to the national electorate (race ≈ White 77% / Black 10% / Hispanic 8% / Asian 4% / Native 1%; age-weighted toward ~35% 65-plus; with party, education, and ideology crossed in). Each archetype evaluates message pairs in character and selects the more convincing of the two, across roughly 6,300 head-to-head comparisons in a single pass with no optimization toward target numbers. A calibrated 10–15% “unexpected-choice” rate is built in to reproduce real-respondent inconsistency and to hold the top-to-bottom spread to the 30–40 points observed in fielded MaxDiff studies rather than an artificially wide split. One cell is thin this period: the aspirational register’s 12.9% rests on a single message — read it as directionally weak, not precisely measured.

A message’s selection rate is the share of its head-to-head appearances it wins; rates are then aggregated by frame, antagonist, register, and argument-element, and the lift of each ingredient is the difference in average selection rate between messages that carry it and those that do not. Results are reported two ways: likely-voter-weighted (the message, register, antagonist, and ingredient cuts) and re-weighted to the engagement-reached audience (the frame cut), the latter by applying the audience model’s gender/age distribution for the content these attacks actually reach. This is a synthetic panel — archetype responses are model-simulated, not live human interviews — calibrated against prior human benchmarks and held to realistic spreads. Read it as message triage that prioritizes what to put into live testing, not as a substitute for a fielded poll.

Diffusion: Originators vs. Amplifiers

The originator/amplifier analysis separates the accounts that start a story from those that give it the most reach. It runs in two passes. First, near-duplicate clustering: every post’s text is normalized (URLs, @-handles, casing, and punctuation stripped) and grouped with near-identical posts, so the same claim or clip is tracked as it reappears across accounts — a window’s posts collapse into a few thousand recurring-story clusters covering roughly 40% of volume. Second, native amplifier edges: the platform-level quote, reply, and repost relationships (present on about 36% of posts) link each amplifying post to the item it echoes.

Within a cluster, the originator is the earliest poster (or, for a retweet/quote chain, the account being quoted); downstream reach is the total engagement the story accrues beyond the originator’s own post; amplifiers are the other accounts in the cluster, ranked by the reach they add to stories they did not start. Originators are ranked both by the number of distinct stories they seed and by the downstream reach those seeds generate. Caveats: only content with a captured native edge (~36%) contributes to the edge-based view; text clustering misses heavy paraphrase and cross-language restatement; and “originator” is the earliest post in the dataset, which can trail an off-platform or unmonitored origin.

Audience Model

Because the dashboard captures no engager-level data, audience is modeled from the accounts that produce and amplify each slice of content, engagement-weighted, under a homophily assumption (producer ≠ audience is the foundational caveat). It blends US Census surname distributions (race), Social Security first-name records (gender and age), each platform’s known user base, and account location. The evidence share reports the fraction of reach carried by accounts with a real name or hand-labeled seed match rather than a national-average fallback; confidence is the engagement-weighted mean of per-account model confidence. Race is the weakest layer and is hedged hardest. Legal characterizations of the June 30 ruling follow the decision and TFA’s published message guidance: it permits state sports bans, does not require them, does not reach Title IX outside sports, and does not decide whether schools may choose inclusion.