Inverse55%

'Strange New Worlds' Season 4 Review: Star Trek Takes A Victory Lap 74%

By Ryan Britt32%

7/22/2026, 1:00:28 PM

BS Summary: This article contains 30 faulty reasoning types, including Optimism Bias, Post Hoc (False Cause), and Hasty Generalization, with Biased Writer Voice as the most egregious example at 59% saturation with 519 hits. Analysis detected 1,781 faulty-reasoning hits from 880 analyzed words, generating a BS Score of 65.6% and a BS Rank of 74% (5,865 of 21,886 articles). This article is worse (more manipulative) than 73.20% of the article peer group.

Calling Star Trek: Strange New Worlds self-referential would be an understatement. 
But much like many modern Star Treks, at a certain point after all the Easter eggs and callbacks to bygone eras, some of what can be read as references to older Star Trek are also now simply a part of the modern show itself. 
Although Strange New Worlds Season 4 has more “legacy” characters in the regular cast than “new” characters, folks like Captain Pike (Anson Mount) and Number One (Rebecca Romijn) don’t really feel like new versions of characters that come from the 1964 Star Trek pilot episode, “The Cage. 
Eight years after the USS Enterprise appeared in the finale of Star Trek: Discovery Season 1, and four years after the debut of the spinoff that was, at one point, called by the fans, “the Pike show,” these people simply feel like Strange New Worlds characters. 
And in Season 4, the show has delivered what feels like its most consistent set of episodes since Season 1. 
If Strange New Worlds Season 4 would have debuted in the 1990s, it would have felt like the front end of a solid season of Star Trek: The Next Generation. 
Although The Original Series is, in theory, the show that SNW imitates the most closely, with a zany sci-fi concept of the week, it’s actually The Next Generation which reveals its true structure, especially in Season 4. 
While Season 3 had a loose arc about a few Big Bads (the Gorn, the Vezda) , Season 4 is more content to mostly just focus on character stories. 
We get a few much-welcome Una episodes, reminding fans just how much star power Rebecca Romijn has, and suggesting that perhaps she’s been a bit underutilized in previous seasons. 
There’s also Scotty (Martin Quinn) and Ortegas (Melissa Navia) romp, an episode that seems to focus on everything that’s bothering James T. 
Kirk (Paul Wesley), and of course, there’s the puppet episode, which, is actually focused on the return of a character we haven’t seen in awhile. 
And, as always, there’s lots of Spock, and Ethan Peck has never been better. 
This is all to say that I could describe SNW Season 4 as a collection of different genres: a noir episode, a dinosaur episode, horror, and so forth. 
But the true reason why the season clicks is because the characters feel so fully developed now that SNW is, like TNG before it, a people show. 
Famously, Next Generation producer, the late Michael Piller, changed the paradigm of that series in Season 3, to suggest episodes focus on specific characters, rather than big sci-fi ideas. 
This single shift probably defined more of Star Trek than fans realize. 
While most contemporary sci-fi series are generally stuck in the season-long-arc prestige format, the Star Trek franchise, even in the streaming era, has managed to retain some of its TNG-era character-centric focus. 
And so, Season 4 becomes a charming synthesis of modern TV sensibilities and the magic of 1990s era Star Trek. 
(Which, if you squint, lasted from 1987 to 2005). 
What fans talk about when they talk about good Star Trek is generally focused on the idea of optimism, a hopeful future, cool sci-fi concepts, and color-coded outfits. 
But the optimism and uniforms are the reasons folks come up with when trying to figure out why Star Trek is still such a cult hit, 60 years later. 
The truth is, good Star Trek characters, when well-written and realized by great actors, are unlike any other characters in TV. 
Was the character of M’Benga particularly interesting when he appeared in “A Private Little War” in The Original Series? 
Well, it’s debatable. 
But, TOS would have never given us an entire M’Benga episode, and now thanks to SNW, we have several; one moment smack dab in the middle of Season 4, Babs Olusanmokun manages to top himself. 
Ditto Jess Bush, who has made Nurse Chapel far more dimensional than she ever was on TOS. 
And though he still feels new to the cast, Martin Quinn has already embedded Scotty with more pathos and introspection than James Doohan was ever allowed to. 
This isn’t to say Strange New Worlds Season 4 is somehow the best season of Star Trek ever. 
It’s not. 
Like all the seasons, some episodes will be perfectly attuned to some fans’ tastes, while others will appeal to different viewers altogether. 
The achievement of this collection of episodes is that, on the 60th anniversary year of Star Trek, Strange New Worlds manages to play the hits of the franchise, while also being true to the characters that it has created, nurtured, and reinvented. 
This is, after all, the last regular season of Strange New Worlds before the end. 
In Season 5, the series will come to a close, with six episodes instead of 10. 
Next year, the pressure will be on, and Trekkie scrutiny will be high. 
But for now, this quirky collection of star voyagers are having the time of their lives. 
It’s too bad after this year, there’s only one more season. 
We could have easily had 50 more episodes with this crew. 
Star Trek: Strange New Worlds Season 4 hits Paramount+ on July 24. 
Article reasoning-pattern comparisonThis article: 0.0%Ryan Britt: 3.0%Inverse: 4.0%Confirmation Bias0.0%This article: 0.0%Ryan Britt: 0.8%Inverse: 0.8%Anchoring Bias0.0%This article: 8.5%Ryan Britt: 3.5%Inverse: 3.6%Availability Heuristic8.5%This article: 6.9%Ryan Britt: 1.5%Inverse: 1.5%Representativeness Heuristic6.9%This article: 3.4%Ryan Britt: 2.1%Inverse: 2.3%Hindsight Bias3.4%This article: 1.4%Ryan Britt: 2.3%Inverse: 2.8%Overconfidence Bias1.4%This article: 5.0%Ryan Britt: 3.0%Inverse: 4.7%Framing Effect5.0%This article: 1.3%Ryan Britt: 0.4%Inverse: 0.6%Loss Aversion1.3%This article: 0.0%Ryan Britt: 0.5%Inverse: 0.7%Status Quo Bias0.0%This article: 5.2%Ryan Britt: 0.3%Inverse: 0.5%Sunk Cost Effect5.2%This article: 14.3%Ryan Britt: 3.3%Inverse: 3.8%Optimism Bias14.3%This article: 0.3%Ryan Britt: 0.7%Inverse: 2.1%Pessimism Bias0.3%This article: 4.8%Ryan Britt: 3.4%Inverse: 8.7%Negativity Bias4.8%This article: 0.0%Ryan Britt: 0.7%Inverse: 0.6%Self-Serving Bias0.0%This article: 0.0%Ryan Britt: 0.0%Inverse: 1.1%Fundamental Attribution Error0.0%This article: 3.1%Ryan Britt: 0.1%Inverse: 0.2%Actor-Observer Bias3.1%This article: 3.2%Ryan Britt: 1.7%Inverse: 0.8%In-Group Bias3.2%This article: 0.0%Ryan Britt: 0.0%Inverse: 0.2%Out-Group Homogeneity Bias0.0%This article: 4.9%Ryan Britt: 4.0%Inverse: 5.4%Halo Effect4.9%This article: 0.0%Ryan Britt: 0.1%Inverse: 0.2%Horn Effect0.0%This article: 0.0%Ryan Britt: 0.0%Inverse: 0.0%Dunning-Kruger Effect0.0%This article: 0.0%Ryan Britt: 1.2%Inverse: 1.9%Recency Bias0.0%This article: 5.3%Ryan Britt: 0.8%Inverse: 0.8%Primacy Effect5.3%This article: 2.5%Ryan Britt: 0.2%Inverse: 0.1%Blind-Spot Bias2.5%This article: 0.0%Ryan Britt: 0.0%Inverse: 0.4%Ad Hominem0.0%This article: 0.0%Ryan Britt: 0.0%Inverse: 0.2%Straw Man0.0%This article: 3.3%Ryan Britt: 1.5%Inverse: 2.7%Appeal to Authority3.3%This article: 3.3%Ryan Britt: 1.5%Inverse: 2.1%False Dilemma3.3%This article: 1.5%Ryan Britt: 0.4%Inverse: 0.6%Slippery Slope1.5%This article: 0.0%Ryan Britt: 0.5%Inverse: 0.5%Circular Reasoning0.0%This article: 10.9%Ryan Britt: 5.1%Inverse: 8.0%Hasty Generalization10.9%This article: 0.0%Ryan Britt: 0.0%Inverse: 0.1%Red Herring0.0%This article: 3.2%Ryan Britt: 0.9%Inverse: 0.9%Bandwagon3.2%This article: 4.3%Ryan Britt: 2.3%Inverse: 4.2%Appeal to Emotion4.3%This article: 0.0%Ryan Britt: 0.7%Inverse: 1.1%Begging the Question0.0%This article: 11.5%Ryan Britt: 1.8%Inverse: 3.4%Post Hoc (False Cause)11.5%This article: 0.0%Ryan Britt: 0.0%Inverse: 0.0%Tu Quoque0.0%This article: 0.0%Ryan Britt: 0.5%Inverse: 0.5%Burden of Proof0.0%This article: 0.0%Ryan Britt: 0.1%Inverse: 0.1%Appeal to Nature0.0%This article: 4.8%Ryan Britt: 0.5%Inverse: 0.6%Composition/Division4.8%This article: 5.2%Ryan Britt: 0.6%Inverse: 1.3%Anecdotal5.2%This article: 9.3%Ryan Britt: 0.3%Inverse: 0.2%No True Scotsman9.3%This article: 9.2%Ryan Britt: 2.4%Inverse: 2.5%Ambiguity (Equivocation)9.2%This article: 0.0%Ryan Britt: 0.0%Inverse: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Ryan Britt: 0.2%Inverse: 0.3%Middle Ground0.0%This article: 0.0%Ryan Britt: 0.2%Inverse: 0.1%Personal Incredulity0.0%This article: 0.0%Ryan Britt: 0.1%Inverse: 0.1%Special Pleading0.0%This article: 0.0%Ryan Britt: 0.0%Inverse: 0.1%Genetic Fallacy0.0%This article: 3.3%Ryan Britt: 0.6%Inverse: 1.6%Unattributed Quote3.3%This article: 2.2%Ryan Britt: 0.5%Inverse: 0.5%Quote-first Misdirection2.2%This article: 59.0%Ryan Britt: 17.1%Inverse: 21.3%Biased Writer Voice59.0%This article: 0.0%Ryan Britt: 0.9%Inverse: 1.5%Indoctrination0.0%This article: 0.0%Ryan Britt: 0.0%Inverse: 0.2%Politically Left Leaning Bias0.0%This article: 0.0%Ryan Britt: 0.0%Inverse: 0.0%Politically Right Leaning Bias0.0%This article: 1.4%Ryan Britt: 1.7%Inverse: 2.0%Attempt to Sell a Product or S…1.4%

880 words analyzed.

Speakers

1speaker3.3%attributed speech851writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 12 words • 100.0% coverageWriter's voice • 11 words • 100.0% coverageWriter's voice • 44 words • 100.0% coverageWriter's voice • 47 words • 100.0% coverageWriter's voice • 46 words • 0.0% coverageWriter's voice • 20 words • 100.0% coverageWriter's voice • 30 words • 0.0% coverageWriter's voice • 37 words • 100.0% coverageWriter's voice • 29 words • 0.0% coverageWriter's voice • 29 words • 100.0% coverageWriter's voice • 22 words • 100.0% coverageWriter's voice • 25 words • 0.0% coverageWriter's voice • 14 words • 100.0% coverageWriter's voice • 28 words • 0.0% coverageWriter's voice • 27 words • 100.0% coverageMichael Piller • 29 words • 100.0% coverageWriter's voice • 12 words • 100.0% coverageWriter's voice • 32 words • 0.0% coverageWriter's voice • 20 words • 0.0% coverageWriter's voice • 9 words • 0.0% coverageWriter's voice • 28 words • 100.0% coverageWriter's voice • 29 words • 100.0% coverageWriter's voice • 21 words • 100.0% coverageWriter's voice • 19 words • 100.0% coverageWriter's voice • 3 words • 0.0% coverageWriter's voice • 35 words • 100.0% coverageWriter's voice • 17 words • 100.0% coverageWriter's voice • 27 words • 100.0% coverageWriter's voice • 18 words • 100.0% coverageWriter's voice • 2 words • 0.0% coverageWriter's voice • 22 words • 0.0% coverageWriter's voice • 42 words • 100.0% coverageWriter's voice • 15 words • 0.0% coverageWriter's voice • 16 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageWriter's voice • 16 words • 100.0% coverageWriter's voice • 11 words • 0.0% coverageWriter's voice • 11 words • 100.0% coverageWriter's voice • 12 words • 100.0% coverage
Selected voice

Michael Piller

100%flagged-word coverage
29 attributed words100% of attributed speech89% writer coverage
0%50.0%100.0%Unattributed Quote+100.0 ptsWriter: 0.0%Michael Piller: 100.0%100.0%Biased Writer Voice-61.0 ptsWriter: 61.0%Michael Piller: 0.0%0.0%Quote-first Misdirection-2.2 ptsWriter: 2.2%Michael Piller: 0.0%0.0%Attempt to Sell a Product -1.4 ptsWriter: 1.4%Michael Piller: 0.0%0.0%

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

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Analysis

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