Policy criticism
The text of this post is on X; follow the source link to read it.
Jun 7, 2026 · Posts on X (state legislators) · policy criticism; policy discussion; Health · Source
0.74
agreement between talk and bills (0 to 1), in the top 5% of State House Democrats
Agreement 0.74 on a 0–1 scale; the average for State House Democrats is 0.54. Ranks 4th of 503, where 1st is the closest match.
How closely the mix of policy areas in McDonald’s statements matches the mix in the bills McDonald sponsors and cosponsors: 1 means the same areas in the same proportions, 0 means no overlap. Ranked among State House Democrats.
At a glance
6 measures against State House Democrats. 7.1% of McDonald’s statements use bipartisan language, 2.5 times the State House Democrat average of 2.9%. McDonald sits at −0.35 on the CSIP scale, more conservative than 87% of State House Democrats.
The measures on which McDonald sits furthest from the middle of State House Democrats, each against the same group, with the CSIP score when there is one. Every number is explained in its own section below.
Talk-to-bills agreement
0.74
State House Democrats average 0.54 · ranks 4th of 503
Attendance
100%
New York House average 93.9% · ranks 10th of 149 · 2,019 roll calls
Bipartisanship
7.1%
State House Democrats average 2.9% · ranks 70th of 764
CSIP ideology
−0.35
More conservative than 87% of State House Democrats · ± 0.03
Out of committee
35%
New York House average 20% · ranks 20th of 148
Extreme labels
0%
State House Democrats average 1.0% · ranks 543rd of 764
Peer group: State House Democrats. Rank 1 is the highest value in the group; the thick bar is McDonald, the thin grey bar the peer average. The headline is the measure on which McDonald is most unusual among peers (Methods, §08).
What McDonald says
McDonald attacks opponents personally about as often as the median State House Democrat. Personal attacks in 0.5% of 406 statements, against 2.5% for the average State House Democrat; 372nd of 764.
An AI model reads each of McDonald’s 406 statements in the NY 2025–26 session (406 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 House Democrats and ranked among them.
Kinds of statement
Share of statements carrying each label, the NY 2025–26 session
0%80%
McDonald
Peers
Rank
Policy discussion195 statements
48%
39%
245th of 764
Credit claiming73 statements
18%
14%
271st of 764
Policy criticism34 statements
8%
10%
359th of 764
Bipartisanship29 statements
7%
3%
70th of 764
Personal attacks2 statements
0%
3%
372nd of 764
Show the data
| Row | McDonald | Peers |
|---|---|---|
| Policy discussion | 48% | 39% |
| Credit claiming | 18% | 14% |
| Policy criticism | 8% | 10% |
| Bipartisanship | 7% | 3% |
| Personal attacks | 0% | 3% |
406
statements classified
406 posts on X.
Show the data
| Part | Value |
|---|---|
| posts on X | 406 |
How to read the bars
The thick bar is McDonald; the thin grey bar is the average State House Democrats. A longer thick bar means McDonald does this more than peers. Rank 1 is the highest rate in the group.
Extreme labels
McDonald used no extreme labels in 406 statements. The peer average is 1.0%.
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 NY 2025–26 session
Show the data
| Column | Statements | Personal attacks | Policy criticism | Policy discussion | Bipartisanship | Credit claiming | Extreme labels |
|---|---|---|---|---|---|---|---|
| Jan ’25 | 34 | 0.0% | 14.7% | 55.9% | 11.8% | 26.5% | 0.0% |
| Feb ’25 | 21 | 0.0% | 9.5% | 52.4% | 0.0% | 19.1% | 0.0% |
| Mar ’25 | 53 | 0.0% | 13.2% | 39.6% | 7.5% | 13.2% | 0.0% |
| Apr ’25 | 27 | 7.4% | 11.1% | 55.6% | 14.8% | 14.8% | 0.0% |
| May ’25 | 26 | 0.0% | 3.9% | 42.3% | 3.9% | 34.6% | 0.0% |
| Jun ’25 | 35 | 0.0% | 17.1% | 62.9% | 8.6% | 34.3% | 0.0% |
| Jul ’25 | 26 | 0.0% | 3.9% | 42.3% | 0.0% | 7.7% | 0.0% |
| Aug ’25 | 8 | — (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 | 13 | 0.0% | 0.0% | 23.1% | 15.4% | 7.7% | 0.0% |
| Oct ’25 | 16 | 0.0% | 0.0% | 43.8% | 6.3% | 37.5% | 0.0% |
| Nov ’25 | 16 | 0.0% | 6.3% | 62.5% | 12.5% | 6.3% | 0.0% |
| Dec ’25 | 14 | 0.0% | 28.6% | 42.9% | 0.0% | 0.0% | 0.0% |
| Jan ’26 | 18 | 0.0% | 5.6% | 77.8% | 5.6% | 0.0% | 0.0% |
| Feb ’26 | 9 | — (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 | 11 | 0.0% | 0.0% | 54.5% | 0.0% | 45.5% | 0.0% |
| Apr ’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) |
| May ’26 | 11 | 0.0% | 0.0% | 36.4% | 36.4% | 0.0% | 0.0% |
| Jun ’26 | 8 | — (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 | 14 | 0.0% | 0.0% | 57.1% | 7.1% | 21.4% | 0.0% |
| Aug ’26 | 10 | 0.0% | 0.0% | 30.0% | 0.0% | 20.0% | 0.0% |
| Sep ’26 | 20 | 0.0% | 0.0% | 55.0% | 5.0% | 10.0% | 0.0% |
| Oct ’26 | 10 | 0.0% | 0.0% | 40.0% | 0.0% | 20.0% | 0.0% |
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 NY 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%. 4 months are hatched here.
In McDonald’s words
Real statements from the classifier’s example set, with the labels it assigned
Bipartisanship
The text of this post is on X; follow the source link to read it.
Sep 13, 2026 · Posts on X (state legislators) · policy discussion; bipartisanship; Science, Technology, Communications; Government Operations and Politics · Source
Personal attacks
The text of this post is on X; follow the source link to read it.
Apr 18, 2025 · Posts on X (state legislators) · personal attacks; policy discussion; credit claiming; Health; target: HHS Secretary · 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.
Posts on X (state legislators)
The text of this post is on X; follow the source link to read it.
personal attacks · policy discussion · credit claiming · Health · target: HHS SecretarySource
Posts on X (state legislators)
The text of this post is on X; follow the source link to read it.
personal attacks · policy discussion · Health · target: RFK Jr.Source
All 406 statements
Newest first, the NY 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: 406 posts on X.
Policy
Health is what McDonald talks about most: 32% of policy statements, 2.2 times the peer share. Talk and legislation agree at 0.74 on a 0–1 scale (State House Democrats average 0.54; 4th of 503).
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 McDonald talks about. The bills McDonald sponsors and cosponsors carry the same areas, so the two can be compared.
What McDonald talks about
Share of policy statements by area, the NY 2025–26 session
0%36%
McDonald
Peers
Health63 statements
32%
15%
Government Operations and Politics26 statements
13%
15%
Economics and Public Finance17 statements
9%
11%
Transportation and Public Works15 statements
8%
5%
Commerce14 statements
7%
3%
Show the data
| Row | McDonald | Peers |
|---|---|---|
| Health | 32% | 15% |
| Government Operations and Politics | 13% | 15% |
| Economics and Public Finance | 9% | 11% |
| Transportation and Public Works | 8% | 5% |
| Commerce | 7% | 3% |
How to read the bars
The thick bar is the share of McDonald’s policy statements in an area; the thin grey bar is the average share for State House Democrats. 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 36%. Grey ticks are the State House Democrats averages.
Show the data
| Area | Talks about | State House Democrats, talks about | Legislates on | State House Democrats, legislates on |
|---|---|---|---|---|
| Health | 32% | 15% | 32% | 15% |
| Government Operations and Politics | 13% | 15% | 11% | 8% |
| Economics and Public Finance | 9% | 11% | 1% | 2% |
| Transportation and Public Works | 8% | 5% | 4% | 5% |
| Commerce | 7% | 3% | 5% | 4% |
0.74
talk-to-bills agreement, 0 to 1
State House Democrats average 0.54. Ranks 4th of 503.
What agreement means, and what it doesn’t
Agreement is 1 minus the distance between the two distributions (Jensen–Shannon): 1 means McDonald legislates on exactly the areas McDonald 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 McDonald sponsored count fully, cosponsored bills a quarter. Shown with at least 20 policy statements and 5 bills.
Ideology
McDonald sits at −0.35 on the CSIP scale, left of 0, more conservative than 87% of State House Democrats. Approximate range −0.39 to −0.32, which understates the uncertainty; from 0 donors and 1,191 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”.
−0.35
CSIP ideal point
Approximate range −0.39 to −0.32. From 0 donors and 1,191 roll calls. Run 2026-10-25T215945. Blue is left of 0, red right of 0.
The outlined dot is McDonald, 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 McDonald’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 McDonald sits
Every official in each group, on the CSIP scale
State House Democrats2,392 · median −0.6
New York House150 · median −0.5
All State House5,324 · median +0.1
Show the data
| Group | Officials | Median | Share left of McDonald |
|---|---|---|---|
| State House Democrats | 2392 | −0.6 | 87% |
| New York House | 150 | −0.5 | 55% |
| All State House | 5324 | +0.1 | 39% |
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 McDonald 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 McDonald.
Money
No campaign-finance data.No campaign-finance records are matched to this official.
Votes
McDonald voted with the majority of New York House Democrats on 97.7% of party-line votes and missed none of 2,019 roll calls. New York House on average: 92.9% party unity, 93.9% attendance. Across all roll calls, McDonald voted against the majority of New York House Democrats 10 times.
2,019 roll calls McDonald could vote on in the NY 2025–26 session, compared with New York House. 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 McDonald voted with the majority of New York House Democrats. The count of votes against that majority covers every roll call where the majority took a side.
10
votes against the majority of New York House Democrats
Party unity 97.7%, New York House average 92.9%, ranks 70th of 149. 2,019 roll calls in the NY 2025–26 session.
Attendance and party unity
The thick bar is McDonald, the thin grey bar the New York House average. The scale runs from 80% to 100% to show the gap.
80%100%
McDonald
Peers
Rank
Attendance
100%
93.9%
10th of 149
Party unity
97.7%
92.9%
70th of 149
Show the data
| Row | McDonald | Peers |
|---|---|---|
| Attendance | 100% | 93.9% |
| Party unity | 97.7% | 92.9% |
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 NY 2025–26 session
| Party split (yea–nay) | Why it’s key | |||||
|---|---|---|---|---|---|---|
| Jun 5, 2026 | Yea | With majority | pass | D 86–0 · R 43–0Democrats 86 yea, 0 nay; Republicans 43 yea, 0 nay | became law | |
| Jun 5, 2026 | S 10001 Provides for a license to sell liquor at retail for consumption on certain premises Assembly Vote | Yea | With majority | pass | D 85–2 · R 43–0Democrats 85 yea, 2 nay; Republicans 43 yea, 0 nay | became law |
| Jun 5, 2026 | S 10655 Relates to the compensation, benefits and other terms and conditions of employment of certain state officers and employees; repealer Assembly Vote | Yea | With majority | pass | D 86–0 · R 43–0Democrats 86 yea, 0 nay; Republicans 43 yea, 0 nay | became law |
| Jun 5, 2026 | Yea | With majority | pass | D 64–23 · R 30–13Democrats 64 yea, 23 nay; Republicans 30 yea, 13 nay | became law · party crossover | |
| Jun 5, 2026 | Yea | With majority | pass | D 66–21 · R 30–13Democrats 66 yea, 21 nay; Republicans 30 yea, 13 nay | became law · party crossover |
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 McDonald most often
- Amy PaulinD1,989 shared votes100%
- Andrew HevesiD1,879 shared votes100%
- Amanda SeptimoD1,626 shared votes100%
- Tony SimoneD1,993 shared votes100%
- Steve OtisD1,987 shared votes100%
Votes least often with
The colleagues who voted the same way as McDonald least often
- Dave DiPietroR1,983 shared votes72%
- Chris FriendR1,835 shared votes74%
- Sam PirozzoloR1,995 shared votes79%
- Ari BrownR1,928 shared votes79%
- Lester ChangR2,014 shared votes79%
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
NY 2025–26 session, loads in batches
Legislation
McDonald sponsored 137 bills in the NY 2025–26 session; 14 became law. Cosponsored 474 others. 35% of sponsored bills got out of committee (New York House average 20%; 20th of 148).
The bills McDonald sponsored and cosponsored in the NY 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 NY 2025–26 session
Show the data
| Role | Introduced | In committee | Passed one chamber | Passed both chambers | Became law |
|---|---|---|---|---|---|
| Sponsored | 137 | 137 | 48 | 24 | 14 |
| Cosponsored | 474 | 474 | 79 | 56 | 14 |
How to read the blocks
Ink blocks are bills McDonald sponsored, ochre blocks bills McDonald cosponsored; the figure above each block is the count. Most bills in any legislature never leave committee, so a short staircase is the norm.
35%
of sponsored bills got out of committee
New York House average 20%. Ranks 20th of 148.
Cosponsorship partners
Colleagues who most often cosponsor with McDonald, by number of shared bills in the NY 2025–26 session; the square shows their party.
- Judy Griffin109
- MaryJane Shimsky108
- Phil Steck100
- Jo Anne Simon98
- Carrie Woerner97
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 McDonald’s bills; the toggle shows more.
Bill list
Sponsored and cosponsored, with status and policy area; five are shown, the toggle shows the rest
| A 11548 | Provides that immediate injunctive relief, restraining orders, or cease and desist orders may be sought in cases where voter intimidation, deception or obstruction occurs | Cosponsor | Jun 1, 2026 | In committee | Civil Rights and Liberties, Minority Issues(model) | REFERRED TO ELECTION LAW Jun 1, 2026 |
| A 11521 | Enacts the New York prediction market regulation act | Sponsor | May 28, 2026 | In committee | Finance and Financial Sector(model) | REFERRED TO RACING AND WAGERING May 28, 2026 |
| K 1484 | Commending the Town of Waterford upon the occasion of hosting its 27th Annual Tugboat Roundup from September 11-13, 2026 | Sponsor | May 28, 2026 | Passed one chamber | Unassigned | ADOPTED May 28, 2026 |
| A 11425 | Relates to establishing a statewide multi-agency integrated data system for certain violations relating to motor vehicle registration and use | Cosponsor | May 15, 2026 | In committee | Transportation and Public Works(model) | REFERRED TO TRANSPORTATION May 15, 2026 |
| A 11430 | Authorizes the commissioner of education to conduct a study regarding the mass starvation in Ireland from 1845 until 1850 | Cosponsor | May 15, 2026 | In committee | Education(model) | REFERRED TO EDUCATION May 15, 2026 |
Online
A site that changed 1 time in 90 days. McDonald’s official site had 1 page when last crawled on Oct 1, 2026.
The lab crawls McDonald’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 McDonald posts with a vision model.
Websites
- 1
pages crawled
1changes in 90 days
- 10
pages crawled
15changes 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 McDonald posted
No images from McDonald’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
859 turns, Jan 23, 2020 to Jun 5, 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 McDonald is most unusual among State House Democrats, 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
- 0ce05d4e-e231-4d3e-8ba5-179499230adc
- Open States
- ocd-person/0ce05d4e-e231-4d3e-8ba5-179499230adc
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