Judge grants partial victory in Philadelphia write-in votes lawsuit 27%

By Meir Rinde24%

7/20/2026, 7:32:35 PM

BS Summary: This article contains 24 faulty reasoning types, including Ambiguity (Equivocation), Framing Effect, and Appeal to Authority, with Negativity Bias as the most egregious example at 18% saturation with 169 hits. Analysis detected 1,186 faulty-reasoning hits from 939 analyzed words, generating a BS Score of 38.6% and a BS Rank of 27% (15,971 of 21,886 articles). This article is better (less manipulative) than 73.00% of the article peer group.

A judge has given a partial victory to a West Philadelphia lawyer who sued the city over a change in election rules  but the dispute still remains far from settled. 
Four Republicans who ran for their local ward committees in the May primary election are the winners of their races, despite receiving as few as two write-in votes, Court of Common Pleas Judge Jessica Brown said in an order issued last week. 
Earlier this year the City Commissioners, who make up Philadelphia’s Board of Elections, had voted to bar write-in candidates from winning if they received fewer than 10 votes. 
But Brown agreed with Republican election lawyer Matt Wolfe that the commissioners were not following the correct provision of state election law. 
In many Philadelphia wards, there are so few Republicans that it’s virtually impossible for candidates to get on the ballot or receive 10 write-in votes. 
In much of the city, the Republican committees already don’t exist for lack of members, and allowing write-ins to win with just one or two votes is essential to keeping the party alive and relevant, Wolfe argued. 
Only 302 Republican committee members were elected in the primary, out of 3,406 available positions, he said. 
“I’m very pleased that the judge sees the election code as I see it. 
It’s a win for the committeepeople and the voters who voted for them,” Wolfe said. 
However, Brown only ordered the commissioners to certify the four candidates who sued, and not the many others  potentially numbering in the hundreds, both Democrats and Republicans  who ran write-in campaigns for ward committee and won with fewer than 10 votes. 
That means it’s unclear how other candidates are affected by the order and how it will apply in future elections. 
The write-in vote requirement has been repeatedly litigated over the years, and the judge’s decision could lead to more legal filings, Wolfe said. 
“We’ll see if anybody appeals and how that impacts the implementation of the order,” he said. 
“One might argue that if other committeepeople get closed out, this order may give them some litigation options.” 
The deadline to appeal the decision is this Friday. 
Lisa Deeley, vice chair of the City Commissioners, declined to answer questions about the court order, as did the city’s Law Department. 
An attorney for the Republican City Committee declined to comment and a lawyer for the Democrats did not respond to an email. 
Rules vary from election to election 
In cases about write-in requirements, attorneys and judges point to two different sections of state law. 
The section that Wolfe and Brown cited says party officers like ward members win their races by receiving “a plurality of votes…at a primary”  that is, with the most votes, even if it’s just one write-in vote. 
However, other judges have deferred to a different part of the law that says a candidate can’t be certified the winner “unless the total number of votes cast for said person is equal to or greater than the number of signatures required on a nominating petition for the particular office.” 
For ward committee seats, that’s 10 signatures. 
That’s the position a judge took last week in Greene County, in the very southwest corner of the state, bordering West Virginia. 
Common Pleas Judge Christopher Simms said the petition-signature rule applied to an election for the county Republican committee and canceled the wins of 33 write-in candidates. 
However, Simms still allowed a path for some candidates to be seated. 
He noted that the Greene County Board of Elections has not followed the 10-vote rule consistently , requiring it in 2022 but not in 2018, and he agreed to a consent order between the county Republican committee and the disputed write-in candidates. 
It allows them to individually go to the committee, where “they will be offered the right to seek appointment.” 
Wolfe initially sued over the rule change in May and won, but the city and the Philadelphia Republican party appealed and a Commonwealth Court judge ruled against him , saying the case was premature. 
Using the law to protect incumbents 
While races for ward committee and county party positions are obscure to many voters, Wolfe and others argue they are important because of the key role committees play in elections. 
Committee members vote to endorse candidates for City Council, judge, and other positions and then distribute endorsement lists to voters, which often determines who wins, especially in low-turnout races. 
They also elect the ward leaders who make up the Republican and Democratic city committees that pick party leaders  currently, Democratic chair Bob Brady and Republican chair Vince Fenerty. 
Leaders sometimes seek to enforce the 10-vote rule in an effort to exclude dissident party members from committee positions or protect incumbents. 
In 2018, for example, Philadelphia’s Republican party joined a suit over write-in results after two incumbent GOP ward leaders lost reelection bids due to votes from written-in committee members. 
Wolfe is a frequent critic of Fenerty’s leadership and contends that he has pushed for enforcement of the 10-vote rule to protect his control of the party. 
Fenerty has in the past declined to comment on that claim. 
Wolfe declined to say if he will appeal Brown’s decision himself, but said he will continue his efforts to change how the local Republican party operates. 
“If this ruling stands, I plan to use it to file suit against the city committee,” he said. 
“The fact that Republican City Committee is still opposed to bringing new people in should be baffling to anybody that cares about the city of Philadelphia.” 
Article reasoning-pattern comparisonThis article: 3.0%Meir Rinde: 1.1%Billy Penn: 1.1%Confirmation Bias3.0%This article: 0.0%Meir Rinde: 0.9%Billy Penn: 0.3%Anchoring Bias0.0%This article: 5.8%Meir Rinde: 5.5%Billy Penn: 2.8%Availability Heuristic5.8%This article: 0.0%Meir Rinde: 0.3%Billy Penn: 0.6%Representativeness Heuristic0.0%This article: 0.0%Meir Rinde: 0.5%Billy Penn: 0.5%Hindsight Bias0.0%This article: 1.9%Meir Rinde: 1.6%Billy Penn: 1.1%Overconfidence Bias1.9%This article: 7.7%Meir Rinde: 4.1%Billy Penn: 3.3%Framing Effect7.7%This article: 0.0%Meir Rinde: 1.0%Billy Penn: 0.5%Loss Aversion0.0%This article: 3.0%Meir Rinde: 0.6%Billy Penn: 0.5%Status Quo Bias3.0%This article: 1.9%Meir Rinde: 0.1%Billy Penn: 0.3%Sunk Cost Effect1.9%This article: 3.9%Meir Rinde: 10.9%Billy Penn: 6.1%Optimism Bias3.9%This article: 5.4%Meir Rinde: 1.3%Billy Penn: 0.7%Pessimism Bias5.4%This article: 18.0%Meir Rinde: 4.7%Billy Penn: 2.4%Negativity Bias18.0%This article: 4.4%Meir Rinde: 2.3%Billy Penn: 1.2%Self-Serving Bias4.4%This article: 4.8%Meir Rinde: 0.7%Billy Penn: 0.4%Fundamental Attribution Error4.8%This article: 0.0%Meir Rinde: 0.0%Billy Penn: 0.1%Actor-Observer Bias0.0%This article: 6.0%Meir Rinde: 1.7%Billy Penn: 1.1%In-Group Bias6.0%This article: 0.0%Meir Rinde: 0.0%Billy Penn: 0.0%Out-Group Homogeneity Bias0.0%This article: 0.0%Meir Rinde: 2.6%Billy Penn: 2.9%Halo Effect0.0%This article: 0.0%Meir Rinde: 0.0%Billy Penn: 0.0%Horn Effect0.0%This article: 0.0%Meir Rinde: 0.0%Billy Penn: 0.0%Dunning-Kruger Effect0.0%This article: 4.8%Meir Rinde: 1.8%Billy Penn: 0.7%Recency Bias4.8%This article: 0.0%Meir Rinde: 0.2%Billy Penn: 0.2%Primacy Effect0.0%This article: 0.0%Meir Rinde: 0.0%Billy Penn: 0.0%Blind-Spot Bias0.0%This article: 0.0%Meir Rinde: 0.2%Billy Penn: 0.0%Ad Hominem0.0%This article: 0.0%Meir Rinde: 0.0%Billy Penn: 0.0%Straw Man0.0%This article: 7.7%Meir Rinde: 3.0%Billy Penn: 1.6%Appeal to Authority7.7%This article: 0.0%Meir Rinde: 0.9%Billy Penn: 0.7%False Dilemma0.0%This article: 0.0%Meir Rinde: 0.0%Billy Penn: 0.0%Slippery Slope0.0%This article: 0.0%Meir Rinde: 0.0%Billy Penn: 0.2%Circular Reasoning0.0%This article: 5.8%Meir Rinde: 3.4%Billy Penn: 2.9%Hasty Generalization5.8%This article: 0.0%Meir Rinde: 0.0%Billy Penn: 0.1%Red Herring0.0%This article: 0.0%Meir Rinde: 0.9%Billy Penn: 0.7%Bandwagon0.0%This article: 6.7%Meir Rinde: 8.4%Billy Penn: 3.9%Appeal to Emotion6.7%This article: 4.9%Meir Rinde: 1.0%Billy Penn: 0.3%Begging the Question4.9%This article: 5.5%Meir Rinde: 1.8%Billy Penn: 1.6%Post Hoc (False Cause)5.5%This article: 0.0%Meir Rinde: 0.0%Billy Penn: 0.0%Tu Quoque0.0%This article: 0.0%Meir Rinde: 0.3%Billy Penn: 0.2%Burden of Proof0.0%This article: 0.0%Meir Rinde: 0.0%Billy Penn: 0.0%Appeal to Nature0.0%This article: 0.0%Meir Rinde: 0.0%Billy Penn: 0.1%Composition/Division0.0%This article: 4.5%Meir Rinde: 1.3%Billy Penn: 1.8%Anecdotal4.5%This article: 0.0%Meir Rinde: 0.0%Billy Penn: 0.0%No True Scotsman0.0%This article: 8.6%Meir Rinde: 1.4%Billy Penn: 0.9%Ambiguity (Equivocation)8.6%This article: 0.0%Meir Rinde: 0.0%Billy Penn: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Meir Rinde: 0.0%Billy Penn: 0.0%Middle Ground0.0%This article: 0.0%Meir Rinde: 0.0%Billy Penn: 0.0%Personal Incredulity0.0%This article: 0.0%Meir Rinde: 0.0%Billy Penn: 0.0%Special Pleading0.0%This article: 2.9%Meir Rinde: 0.2%Billy Penn: 0.1%Genetic Fallacy2.9%This article: 1.5%Meir Rinde: 1.8%Billy Penn: 0.9%Unattributed Quote1.5%This article: 1.5%Meir Rinde: 0.7%Billy Penn: 0.5%Quote-first Misdirection1.5%This article: 6.3%Meir Rinde: 1.2%Billy Penn: 3.3%Biased Writer Voice6.3%This article: 0.0%Meir Rinde: 1.0%Billy Penn: 1.0%Indoctrination0.0%This article: 0.0%Meir Rinde: 0.0%Billy Penn: 0.7%Politically Left Leaning Bias0.0%This article: 0.0%Meir Rinde: 0.0%Billy Penn: 0.0%Politically Right Leaning Bias0.0%This article: 0.0%Meir Rinde: 0.7%Billy Penn: 5.3%Attempt to Sell a Product or S…0.0%

939 words analyzed.

Speakers

3speakers27%attributed speech687writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 9 words • 0.0% coverageWriter's voice • 31 words • 100.0% coverageJessica Brown • 42 words • 0.0% coverageWriter's voice • 28 words • 0.0% coverageWriter's voice • 22 words • 0.0% coverageWriter's voice • 25 words • 0.0% coverageMatt Wolfe • 37 words • 0.0% coverageMatt Wolfe • 17 words • 0.0% coverageMatt Wolfe • 14 words • 100.0% coverageMatt Wolfe • 15 words • 0.0% coverageWriter's voice • 43 words • 0.0% coverageWriter's voice • 20 words • 0.0% coverageMatt Wolfe • 23 words • 0.0% coverageMatt Wolfe • 16 words • 0.0% coverageMatt Wolfe • 18 words • 0.0% coverageWriter's voice • 9 words • 0.0% coverageWriter's voice • 22 words • 0.0% coverageWriter's voice • 22 words • 0.0% coverageWriter's voice • 6 words • 0.0% coverageWriter's voice • 16 words • 0.0% coverageWriter's voice • 38 words • 0.0% coverageWriter's voice • 50 words • 0.0% coverageWriter's voice • 7 words • 0.0% coverageWriter's voice • 22 words • 0.0% coverageChristopher Simms • 26 words • 0.0% coverageWriter's voice • 12 words • 0.0% coverageWriter's voice • 42 words • 0.0% coverageWriter's voice • 19 words • 0.0% coverageWriter's voice • 34 words • 0.0% coverageWriter's voice • 6 words • 100.0% coverageWriter's voice • 30 words • 0.0% coverageWriter's voice • 29 words • 0.0% coverageWriter's voice • 30 words • 0.0% coverageWriter's voice • 22 words • 100.0% coverageWriter's voice • 29 words • 0.0% coverageWriter's voice • 27 words • 0.0% coverageWriter's voice • 11 words • 0.0% coverageWriter's voice • 26 words • 0.0% coverageMatt Wolfe • 18 words • 0.0% coverageMatt Wolfe • 26 words • 0.0% coverage
Selected voice

Matt Wolfe

91%flagged-word coverage
184 attributed words73% of attributed speech84% writer coverage
0%5.0%10.0%Biased Writer Voice-8.6 ptsWriter: 8.6%Matt Wolfe: 0.0%0.0%Unattributed Quote+7.6 ptsWriter: 0.0%Matt Wolfe: 7.6%7.6%Quote-first Misdirection+7.6 ptsWriter: 0.0%Matt Wolfe: 7.6%7.6%

Attribution is sentence-level. Pattern percentages are calculated only from words assigned to that voice.

Loading…
Loading…
Loading…

Analysis

Hover over highlighted words in the article to view the associated bias or fallacy analysis.