Policy discussion
The text of this post is on X; follow the source link to read it.
Oct 2, 2026 · Posts on X (state legislators) · policy discussion; credit claiming; Health · Source
$520.2K
in itemized contributions in the 2026 cycle, in the top tenth of State Senate Republicans
The median for State Senate Republicans is $46.2K. Ranks 59th of 936, where 1st raised the most. 452 itemized donors.
Itemized contributions reported to the state in the 2026 cycle, ranked among State Senate Republicans. State filings leave small gifts out, and totals depend on whether the seat is up this cycle.
At a glance
6 measures against State Senate Republicans. 45% of the 22 bills Brown sponsored got out of committee, in the top quarter of the Pennsylvania Senate. 91% of Brown’s itemized money in the 2026 cycle came from Pennsylvania, in the bottom half of State Senate Republicans.
The measures on which Brown sits furthest from the middle of State Senate Republicans, each against the same group, with the CSIP score when there is one. Every number is explained in its own section below.
Itemized, 2026
$520.2K
State Senate Republicans’ median $46.2K · ranks 59th of 936
Out of committee
45%
Pennsylvania Senate average 24% · ranks 7th of 49
Attendance
100%
Pennsylvania Senate average 98.9% · ranks 14th of 50 · 502 roll calls
From Pennsylvania, 2026
91%
Of itemized individual dollars · ranks 553rd of 860 State Senate Republicans
Party unity
97.1%
Pennsylvania Senate average 93.4% · ranks 20th of 50 · 3 votes against the majority of Pennsylvania Senate Republicans
CSIP ideology
+0.36
More conservative than 50% of State Senate Republicans · ± 0.05
Peer group: State Senate Republicans. Rank 1 is the highest value in the group; the thick bar is Brown, the thin grey bar the peer average. The headline is the measure on which Brown is most unusual among peers (Methods, §08).
What Brown says
Brown attacks opponents personally less than 76% of State Senate Republicans. Personal attacks in 0% of 98 statements, against 2.3% for the average State Senate Republican; 272nd of 354.
An AI model reads each of Brown’s 98 statements in the PA 2025–26 session (98 posts on X) and marks the kinds of statement it contains: a personal attack, criticism of a policy, discussion of policy, bipartisanship, credit claiming, and extreme labels. A statement can carry several. Every rate is compared with the average for State Senate Republicans and ranked among them.
Kinds of statement
Share of statements carrying each label, the PA 2025–26 session
0%80%
Brown
Peers
Rank
Policy discussion39 statements
40%
37%
161st of 354
Credit claiming26 statements
27%
15%
64th of 354
Policy criticism9 statements
9%
9%
136th of 354
Bipartisanship5 statements
5%
2%
45th of 354
Personal attacks0 statements
0%
2%
272nd of 354
Show the data
| Row | Brown | Peers |
|---|---|---|
| Policy discussion | 40% | 37% |
| Credit claiming | 27% | 15% |
| Policy criticism | 9% | 9% |
| Bipartisanship | 5% | 2% |
| Personal attacks | 0% | 2% |
98
statements classified
98 posts on X.
Show the data
| Part | Value |
|---|---|
| posts on X | 98 |
How to read the bars
The thick bar is Brown; the thin grey bar is the average State Senate Republicans. A longer thick bar means Brown does this more than peers. Rank 1 is the highest rate in the group.
Extreme labels
Brown used no extreme labels in 98 statements. The peer average is 1.3%.
No extreme labels in this window.
Who gets the labels
Targets named alongside an extreme label, by number of statements
No targets recorded.
What an extreme label is
Calls a politician, a party or a policy “far left”, “far right”, “MAGA”, “extreme”, “radical”, “woke”, “fascist” or “communist”. The target is who or what the label was aimed at. The lists show the five most used labels and targets; the toggle shows the rest.
Month by month
Share of statements per month, the PA 2025–26 session
Show the data
| Column | Statements | Personal attacks | Policy criticism | Policy discussion | Bipartisanship | Credit claiming | Extreme labels |
|---|---|---|---|---|---|---|---|
| Jan ’25 | 17 | 0.0% | 0.0% | 5.9% | 17.6% | 11.8% | 0.0% |
| Feb ’25 | 18 | 0.0% | 33.3% | 55.6% | 5.6% | 5.6% | 0.0% |
| Mar ’25 | 0 | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) |
| Apr ’25 | 4 | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) |
| May ’25 | 2 | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) |
| Jun ’25 | 2 | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) |
| Jul ’25 | 2 | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) |
| Aug ’25 | 2 | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) |
| Sep ’25 | 2 | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) |
| Oct ’25 | 0 | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) |
| Nov ’25 | 1 | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) |
| Dec ’25 | 4 | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) |
| Jan ’26 | 7 | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) |
| Feb ’26 | 6 | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) |
| Mar ’26 | 3 | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) |
| Apr ’26 | 3 | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) |
| May ’26 | 6 | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) |
| Jun ’26 | 7 | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) |
| Jul ’26 | 2 | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) |
| Aug ’26 | 4 | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) |
| Sep ’26 | 4 | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) |
| Oct ’26 | 2 | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) | — (fewer than 10 statements) |
How to read the strips
Each row is one kind of statement; each cell is a month, shaded against that row’s own peak (darker = closer to the peak), with the peak and the latest value written at the right. The top row counts statements. The strip covers every month of the PA 2025–26 session, the same span as the rates above, including months with no statements. A month with fewer than 10 statements is hatched, not shaded: one or two posts would swing its rate to 0% or 100%. 20 months are hatched here; 2 of them have no statements.
In Brown’s words
Real statements from the classifier’s example set, with the labels it assigned
Credit claiming
The text of this post is on X; follow the source link to read it.
Oct 22, 2026 · Posts on X (state legislators) · policy discussion; credit claiming; Commerce; Science, Technology, Communications · Source
Bipartisanship
The text of this post is on X; follow the source link to read it.
Jun 29, 2025 · Posts on X (state legislators) · bipartisanship · Source
Examples by category
Up to five recent statements in each category
Overtly questions a named person’s character, integrity or loyalty, or calls them names. Criticising a record or a policy does not count.
No statements in this category in this window.
All 98 statements
Newest first, the PA 2025–26 session
The full feed
Five statements at a time, newest first; filters apply to the statements loaded so far. Export saves the statements that match. Sources: 98 posts on X.
Policy
Economics and Public Finance is what Brown talks about most: 31% of policy statements, 2.5 times the peer share. Talk and legislation agree at 0.54 on a 0–1 scale (State Senate Republicans average 0.52; 110th of 226).
Each policy statement is tagged by the AI model with one or more of 25 policy areas from the Congressional Research Service list, so the shares say what Brown talks about. The bills Brown sponsors and cosponsors carry the same areas, so the two can be compared.
What Brown talks about
Share of policy statements by area, the PA 2025–26 session
0%35%
Brown
Peers
Economics and Public Finance12 statements
31%
12%
Transportation and Public Works7 statements
18%
6%
Government Operations and Politics6 statements
15%
17%
Health6 statements
15%
9%
Science, Technology, Communications5 statements
13%
3%
Show the data
| Row | Brown | Peers |
|---|---|---|
| Economics and Public Finance | 31% | 12% |
| Transportation and Public Works | 18% | 6% |
| Government Operations and Politics | 15% | 17% |
| Health | 15% | 9% |
| Science, Technology, Communications | 13% | 3% |
How to read the bars
The thick bar is the share of Brown’s policy statements in an area; the thin grey bar is the average share for State Senate Republicans. A statement counts once in each of its areas, so shares can add to more than 100%. The five largest areas are shown; the toggle shows the rest.
Talks about · legislates on
Left: share of statements by policy area. Right: share of bills. Areas in order of their share of statements; both sides run from 0 to 35%. Grey ticks are the State Senate Republicans averages.
Show the data
| Area | Talks about | State Senate Republicans, talks about | Legislates on | State Senate Republicans, legislates on |
|---|---|---|---|---|
| Economics and Public Finance | 31% | 12% | 1% | 3% |
| Transportation and Public Works | 18% | 6% | 6% | 6% |
| Government Operations and Politics | 15% | 17% | 10% | 12% |
| Health | 15% | 9% | 24% | 11% |
| Science, Technology, Communications | 13% | 3% | 2% | 1% |
0.54
talk-to-bills agreement, 0 to 1
State Senate Republicans average 0.52. Ranks 110th of 226.
What agreement means, and what it doesn’t
Agreement is 1 minus the distance between the two distributions (Jensen–Shannon): 1 means Brown legislates on exactly the areas Brown talks about, in the same proportions; 0 means no overlap. It does not say whether the bills match the positions in the statements, only the subjects. Bills Brown sponsored count fully, cosponsored bills a quarter. Shown with at least 20 policy statements and 5 bills.
Ideology
Brown sits at +0.36 on the CSIP scale, right of 0, more conservative than 50% of State Senate Republicans. Approximate range +0.31 to +0.41, which understates the uncertainty; from 750 donors and 1,044 roll calls.
CSIP, the lab’s Common-Space Ideal Point, places every official, federal and state, on one left–right scale, estimated from roll-call votes, who gives money to whom, and the text of statements. Negative is left of 0, positive right of it; 0 is the centre of the scale, not a definition of “moderate”.
+0.36
CSIP ideal point
Approximate range +0.31 to +0.41. From 750 donors and 1,044 roll calls. Run 2026-10-25T215945. Blue is left of 0, red right of 0.
The outlined dot is Brown, coloured by its side of 0 (blue left, red right, deeper further out); the bar through it is the approximate range (±1.96 standard errors), which understates the uncertainty; the grey ticks below are the medians of Brown’s groups. 0 is the centre of the scale, not “moderate” by definition.
What this means, and what it doesn’t
The score summarises how an official votes, who funds them and how they talk, relative to everyone else. It does not grade positions as good or bad, and two officials with the same score can differ on any single issue. The ± range is 1.96 standard errors, which understates the uncertainty: scores whose ranges overlap may not differ at all, and even scores whose ranges do not overlap may not differ.
Where Brown sits
Every official in each group, on the CSIP scale
State Senate Republicans1,083 · median +0.4
Pennsylvania Senate50 · median +0.2
All State Senate1,909 · median +0.1
Show the data
| Group | Officials | Median | Share left of Brown |
|---|---|---|---|
| State Senate Republicans | 1083 | +0.4 | 50% |
| Pennsylvania Senate | 50 | +0.2 | 56% |
| All State Senate | 1909 | +0.1 | 71% |
How to read the strips
Every small dot is one official on the same scale, coloured by its own score (blue left of 0, red right of 0, grey at 0, deeper further out) and spread up and down only to keep dots apart; where a group is crowded the dots overlap, and darker patches mean more officials. The large outlined dot is Brown in every row; the rule is each group’s median. The table under the figure gives the share of each group to the left of Brown.
Money
Brown reported $520.2K in the 2026 cycle, 11.2 times the State Senate Republicans’ median of $46.2K. State filings report no small-donation total. 91% of itemized individual money came from Pennsylvania.
Campaign money from state campaign-finance filings, as aggregates only; the lab never shows an individual donor. Campaigns must report by name every person who gives them more than $200 in a cycle (“itemized”); smaller gifts are reported only as one total (“unitemized”), so donor counts, donor states, employers and occupations describe itemized donors only. State filings report no small-gift total, so these figures add up itemized contributions only.
$520.2K
itemized in the 2026 cycle
From 452 itemized donors. State Senate Republicans’ median $46.2K.
Where the money came from
Each square is one percent of itemized contributions in the 2026 cycle.
- Individuals (itemized)60 squares$312.3K
- PACs and other committees39 squares$205.4K
- Party committees1 squares$2,500
Show the data
| Source | Amount | Share |
|---|---|---|
| Individuals (itemized) | $312.3K | 60.0% |
| PACs and other committees | $205.4K | 39.5% |
| Party committees | $2,500 | 0.5% |
What this means, and what it doesn’t
Totals say how much a campaign took in, not how it was spent, and they rise sharply when a seat is up for election; compare cycles with that in mind.
Receipts by cycle
Itemized contributions, 2020 to 2026. The grey line is the State Senate Republicans’ median for 2026.
Show the data
| Item | Value |
|---|---|
| 2020 cycle | $113.4K |
| 2022 cycle | $1.5M |
| 2024 cycle | $151.2K |
| 2026 cycle | $520.2K |
Top donor states, 2026
Itemized contributions by donor state. 91% came from Pennsylvania.
- Pennsylvania$284.4K
- Wisconsin$10.0K
- Florida$9,300
- Virginia$2,760
- New York$2,400
Small donations
State filings report no total for small gifts.
Not reported in state filings.
Where itemized donors live
Individuals who gave more than $200, by donor state
Show the data
| State | Value |
|---|---|
| Pennsylvania | $284.4K |
| Wisconsin | $10.0K |
| Florida | $9,300 |
| Virginia | $2,760 |
| New York | $2,400 |
| New Jersey | $1,700 |
| North Carolina | $1,304 |
| Georgia | $400 |
| Colorado | $100 |
| Alaska | No data |
| Maine | No data |
| Vermont | No data |
| New Hampshire | No data |
| Washington | No data |
| Idaho | No data |
| Montana | No data |
| North Dakota | No data |
| Minnesota | No data |
| Illinois | No data |
| Michigan | No data |
| Rhode Island | No data |
| Massachusetts | No data |
| Oregon | No data |
| Nevada | No data |
| Wyoming | No data |
| South Dakota | No data |
| Iowa | No data |
| Indiana | No data |
| Ohio | No data |
| Connecticut | No data |
| California | No data |
| Utah | No data |
| Nebraska | No data |
| Missouri | No data |
| Kentucky | No data |
| West Virginia | No data |
| Maryland | No data |
| Delaware | No data |
| Arizona | No data |
| New Mexico | No data |
| Kansas | No data |
| Arkansas | No data |
| Tennessee | No data |
| South Carolina | No data |
| District of Columbia | No data |
| Oklahoma | No data |
| Louisiana | No data |
| Mississippi | No data |
| Alabama | No data |
| Hawaii | No data |
| Texas | No data |
452
itemized donors
People who gave more than $200
91%
from Pennsylvania
Of itemized individual dollars
How to read the map
Every state the same size. Darker states gave more itemized money; hatched states had no itemized donors; the outlined state is Pennsylvania. Gifts of $200 or less carry no address and are left out.
Top donor occupations
Itemized, 2026 cycle.
- SELF EMPLOYED$78.3K 35 donors
- OWNER$69.7K 16 donors
- RETIRED$50.0K 38 donors
- CEO$17.5K 4 donors
- MANAGER$7,541 3 donors
Top committees
PAC and committee contributions, 2026 cycle.
- FRIENDS OF SCOTT MARTIN$50.0K
- PA EDUCATION CHOICE FUND$26.5K
- WIND CREEK BETHLEHEM LLC$17.5K
- CHAMBER PAC$10.0K
- PAA PAC$7,500
Top employers
Itemized, 2026 cycle.
No employers reported.
Aggregates only. Individual donors are never named.
Votes
Brown voted with the majority of Pennsylvania Senate Republicans on 97.1% of party-line votes and missed none of 502 roll calls. Pennsylvania Senate on average: 93.4% party unity, 98.9% attendance. Across all roll calls, Brown voted against the majority of Pennsylvania Senate Republicans 3 times.
502 roll calls Brown could vote on in the PA 2025–26 session, compared with Pennsylvania Senate. Attendance is the share with a vote recorded. Party unity counts only party-line roll calls, where most Democrats and most Republicans voted on opposite sides, and is the share of those where Brown voted with the majority of Pennsylvania Senate Republicans. The count of votes against that majority covers every roll call where the majority took a side.
3
votes against the majority of Pennsylvania Senate Republicans
Party unity 97.1%, Pennsylvania Senate average 93.4%, ranks 20th of 50. 502 roll calls in the PA 2025–26 session.
Attendance and party unity
The thick bar is Brown, the thin grey bar the Pennsylvania Senate average. The scale runs from 80% to 100% to show the gap.
80%100%
Brown
Peers
Rank
Attendance
100%
98.9%
14th of 50
Party unity
97.1%
93.4%
20th of 50
Show the data
| Row | Brown | Peers |
|---|---|---|
| Attendance | 100% | 98.9% |
| Party unity | 97.1% | 93.4% |
What this means, and what it doesn’t
A missed roll call has many causes, from illness to campaigning, so attendance says how often, not why. A vote against the majority can be on procedure as well as substance, and many fall on roll calls where both parties split; the key votes below show the ones that decided something.
Key votes
25 roll calls the lab flagged as key in the PA 2025–26 session
| Party split (yea–nay) | Why it’s key | |||||
|---|---|---|---|---|---|---|
| Oct 21, 2026 | HB 2187 An Act amending the act of April 9, 1929 (P.L.177, No.175), known as The Administrative Code of 1929, in administrative organization, further providing for criminal history background checks of employees and contractors with access to Federal tax information. FINAL PASSAGE | Yea | With majority | pass | D 23–0 · R 27–0Democrats 23 yea, 0 nay; Republicans 27 yea, 0 nay | became law |
| Oct 21, 2026 | HB 558 An Act amending the act of April 6, 1951 (P.L.69, No.20), known as The Landlord and Tenant Act of 1951, in creation of leases, statute of frauds and mortgaging of leaseholds, providing for rental applications. FINAL PASSAGE | Yea | Against majority | pass | D 23–0 · R 13–14Democrats 23 yea, 0 nay; Republicans 13 yea, 14 nay | became law · party crossover |
| Oct 21, 2026 | HB 1098 An Act amending the act of November 22, 1978 (P.L.1166, No.274), referred to as the Pennsylvania Commission on Crime and Delinquency Law, providing for Investigation and Prosecution of Internet Crimes Against Children Program. FINAL PASSAGE | Yea | With majority | pass | D 23–0 · R 27–0Democrats 23 yea, 0 nay; Republicans 27 yea, 0 nay | became law |
| Oct 21, 2026 | SB 807 An Act amending the act of November 6, 1987 (P.L.381, No.79), known as the Older Adults Protective Services Act, in preliminary provisions, further providing for definitions; in administration, further providing for investigations of reports of need for protective services, for immunity from civil a FINAL PASSAGE | Yea | With majority | pass | D 15–8 · R 27–0Democrats 15 yea, 8 nay; Republicans 27 yea, 0 nay | party crossover |
| Oct 21, 2026 | HB 2437 An Act amending Title 58 (Oil and Gas) of the Pennsylvania Consolidated Statutes, in unconventional gas well fee, further providing for Statewide initiatives. FINAL PASSAGE | Yea | With majority | pass | D 22–1 · R 27–0Democrats 22 yea, 1 nay; Republicans 27 yea, 0 nay | became law |
How key votes are chosen
Automatically: a final-passage or override vote where the measure became law, the margin was under 10%, at least 10% of either party voted against its majority, or the bill was among the 25 most mentioned in officials’ own statements. Up to 25 per window, most recent first; five are shown. Bars show yea on the left, nay on the right, per party.
Votes most often with
The colleagues who voted the same way as Brown most often
- Wayne LangerholcR502 shared votes100%
- Joe PittmanR502 shared votes100%
- Kim WardR497 shared votes100%
- Elder VogelR502 shared votes99%
- Devlin RobinsonR502 shared votes99%
Votes least often with
The colleagues who voted the same way as Brown least often
- Katie MuthD484 shared votes69%
- Lindsey WilliamsD502 shared votes73%
- Nikil SavalD502 shared votes75%
- Tim KearneyD499 shared votes76%
- Amanda CappellettiD499 shared votes76%
How to read the agreement lists
The share of roll calls both members voted on where they voted the same way, among colleagues sharing at least 50 such votes. High agreement with members of the other party is common on routine votes.
Full voting record
PA 2025–26 session, loads in batches
Legislation
Brown sponsored 22 bills in the PA 2025–26 session; 2 became law. Cosponsored 382 others. 45% of sponsored bills got out of committee (Pennsylvania Senate average 24%; 7th of 49).
The bills Brown sponsored and cosponsored in the PA 2025–26 session, from the official bill records, and how far each got: introduced, referred to or acted on in committee, passed one chamber, passed both, became law. A bill counts at every stage it has reached, so the blocks only shrink to the right.
Bills by stage
Counts for the PA 2025–26 session
Show the data
| Role | Introduced | In committee | Passed one chamber | Passed both chambers | Became law |
|---|---|---|---|---|---|
| Sponsored | 22 | 22 | 7 | 2 | 2 |
| Cosponsored | 382 | 382 | 88 | 36 | 32 |
How to read the blocks
Ink blocks are bills Brown sponsored, ochre blocks bills Brown cosponsored; the figure above each block is the count. Most bills in any legislature never leave committee, so a short staircase is the norm.
45%
of sponsored bills got out of committee
Pennsylvania Senate average 24%. Ranks 7th of 49.
Cosponsorship partners
Colleagues who most often cosponsor with Brown, by number of shared bills in the PA 2025–26 session; the square shows their party.
- Jay Costa211
- Pat Stefano207
- Tracy Pennycuick202
- Wayne Fontana202
- Elder Vogel198
What this means, and what it doesn’t
The score is the share of sponsored bills that a committee reported out or a chamber passed, with at least 5 sponsored bills, ranked within the peer group. Members of the majority party and committee chairs move more bills, so the rank reflects position in the chamber as well as effort. Cosponsorship partners are the five colleagues who share the most of Brown’s bills; the toggle shows more.
Bill list
Sponsored and cosponsored, with status and policy area; five are shown, the toggle shows the rest
| SB 1041 | An Act amending the act of June 13, 1967 (P.L.31, No.21), known as the Human Services Code, in public assistance, providing for medical assistance for complex care assistant services. | Sponsor | Oct 19, 2026 | In committee | Health(model) | Re-referred to Appropriations Oct 20, 2026 |
| SB 965 | An Act amending Title 35 (Health and Safety) of the Pennsylvania Consolidated Statutes, providing for Maternal Health Monitoring Pilot Program. | Cosponsor | Oct 19, 2026 | In committee | Health(model) | First consideration Oct 19, 2026 |
| SR 398 | A Resolution designating October 24, 2026, as "Acupuncture and Herbal Medicine Day" in Pennsylvania. | Cosponsor | Oct 15, 2026 | In committee | Unassigned | Senate concurred in House amendments Oct 20, 2026 |
| SR 396 | A Resolution recognizing the week of October 25 through 31, 2026, as "Respiratory Care Week" in Pennsylvania. | Cosponsor | Oct 14, 2026 | In committee | Unassigned | Referred to Rules & Executive Nominations Oct 14, 2026 |
| SB 1490 | An Act amending the act of March 4, 1971 (P.L.6, No.2), known as the Tax Reform Code of 1971, in realty transfer tax, further providing for excluded transactions. | Cosponsor | Oct 13, 2026 | In committee | Taxation(model) | Referred to Finance Oct 13, 2026 |
Online
A site that changed 31 times in 90 days. Brown’s official site had 15 pages when last crawled on Oct 1, 2026.
The lab crawls Brown’s official and campaign websites (weekly for Congress, monthly for the states) and keeps every page’s text, so changes can be read later; it also records social accounts and describes the images Brown posts with a vision model.
Websites
- 15
pages crawled
31changes in 90 days
- 1
pages crawled
0changes in 90 days
How to read the counts
“Pages crawled” is the size of the site at the last crawl; “changes in 90 days” counts pages whose text differed from the previous crawl. Sites change for many routine reasons, such as new press releases, so a high count is not by itself notable.
Social accounts
Images Brown posted
No images from Brown’s posts have been described.
About the descriptions
Written by a vision model and may be wrong. Open the post to see the original. Five are shown; the toggle shows the rest.
State floor speeches
86 turns, Jan 14, 2020 to Jul 12, 2026
Floor speeches
Transcribed from chamber video or captions by the lab. They are not classified for kinds of statement.
Methods and sources
How this page was made. Profile built Oct 28, 2026; site last built Oct 28, 2026. Every number on the page is computed from the sources listed here, by the same rules for every official; nothing is written by hand.
The headline
The headline is the measure on which Brown is most unusual among State Senate Republicans, chosen by one rule for every official of every party. The candidates are the rate of each kind of statement and of extreme labels, party unity, attendance, the small-donor share, the in-state share and total receipts of the latest cycle, the share of sponsored bills that got out of committee, talk-to-bills agreement, and the CSIP score’s place within the party group.
The builder ranks every measure within the same peer group the page compares it with, and writes each official’s percentile: the share of the group below the value, ties counting half, so 0.5 is the median and a value shared by many never ranks first. A measure’s score is how far that percentile sits from the median (0 in the middle, 0.5 at either end), and the highest score leads if it is above 0.25, outside the middle half of the group. Scores within 0.03 of each other are a tie, broken in this order: votes against the party majority, kinds of statement, ideology, roll calls missed, small donations, in-state money, legislation, agreement, extreme labels, receipts.
A measure counts only with at least 200 statements, 100 roll calls or 5 sponsored bills behind it and a peer group of at least 10. Two things never lead: high party unity or attendance, where most members sit, and a high rate of a kind of statement backed by fewer than 10 statements. When nothing qualifies, the headline is a neutral fact instead: statements classified, or years in office. The wording always names the direction (“in the bottom 5% of …”, “votes against the majority of …”).
Identifiers
- Profile id
- 3e2840e6-f904-43be-911e-235b906458a5
- Open States
- ocd-person/3e2840e6-f904-43be-911e-235b906458a5
Bulk files with the same data for every official:
Freshness of this profile’s data
- What politicians sayOct 27, 20261 days agoMembers of Congress: tweets since 2017; press releases, newsletters and floor speeches since 2022. State legislators: tweets since May 2024. Governors: tweets since January 2025. Labels from an LLM classifier.
- Roll calls (state)Oct 21, 20267 days agoOpen States floor roll calls, 2019 on (none for AK and MO).
- Bills (state)Oct 28, 2026todayOpen States bills and sponsors, 2019 on; stages from roll calls.
- Campaign money (state)no dateState campaign-finance agencies, 2019 on; aggregates only.
- Ideology (CSIP)Oct 25, 20263 days agoCommon-Space Ideal Points (CSIP), current validated run.
- WebsitesOct 25, 20263 days agoWeekly crawls of federal sites since April 2026; monthly state crawls since June 2026.
- State floor speechesOct 21, 20267 days agoState floor speech turns (published transcripts and captions), 2020 on; not LLM-classified.
How the measures work
- What politicians say
- Every post, press release, newsletter and congressional floor speech is read by a language model and marked for personal attacks, policy criticism, policy discussion, bipartisanship and credit claiming. A statement can be in several. Rates are shares of statements in the window. The methods paper.
- Extreme labels
- A statement has an extreme label when it calls a politician, party or policy “far left”, “far right”, “MAGA”, “extreme”, “radical”, “woke”, “fascist” or “communist”. The target is who the label is aimed at.
- Policy areas and agreement
- Statements and bills share 25 Congressional Research Service policy areas (state bills are assigned by a language model). Agreement is 1 − Jensen–Shannon distance between the two distributions, shown with at least 20 policy statements and 5 bills.
- Ideology (CSIP)
- Common-Space Ideal Points place federal and state officials on one left–right scale, estimated jointly from roll calls, campaign contributions and the text of statements, with standard errors. Only a validated run is shown. The methods paper.
- Campaign money
- Campaigns report by name only donors who give more than $200 in a cycle; smaller gifts are reported as one total. Federal totals and the small-donor share come from the FEC’s financial summaries of each campaign committee. Donor counts, donor states, employers and occupations cover itemized donors only. State filings report no small-gift totals, so state figures are itemized only. The lab never publishes donor names.
- Votes and key votes
- Attendance, party unity and the count of votes against the majority of an official’s own party come from roll calls (Voteview for Congress, chamber records for the states). Key votes are final-passage or override votes that became law, were decided by under 10%, saw at least 10% of a party vote against its majority, or concerned one of the 25 bills most mentioned in officials’ statements.
- Peers and ranks
- Comparisons are with the same party, chamber and level (for example House Democrats); state legislators are compared within their state and chamber for votes. Every comparison names its group. Rank 1 is the highest value in the group; tied values share the average of their ranks, and the percentile is the share of the group below the value, ties counting half.
America’s Political Pulse · Polarization Research Lab