Inside the GOP’s midterm bloodbath

What was read

1732 words in the outlet's own voice, plus 5 in the headline. 2% of the text is in quotes. 6 attribution markers (such as "said" or "according to") found.

Scare quotes (a phrase of one to three words in quotation marks with no speaker in the same sentence): Blue wave, bluenami, Tala-freako,. Since method 3.1.0 their words count as the outlet's own.

Words found

Word choice: obviously 2 points Editorializing
had in the Senate are obviously the big takeaway of the night.
actually 1 point Editorializing
in Alabama. I think it actually shows how Trump’s rigging of the
actually 1 point Editorializing
that worked for them. It actually repositioned the party from the bigger
clearly 2 points Editorializing
that said on it. He’s clearly in his feelings. How bad was
actually 1 point Editorializing
good night. I think that actually matters more for the moderate wing
Raises the temperature: backlash 1 point Raises the temperature
were making up this populist backlash . You have affordability, you have AI,
backlash 1 point Raises the temperature
the game caused an electoral backlash . We can’t overstate that he tried
huge 1 point Raises the temperature
race. The GOP had a huge spending advantage. And it was around
panic 1 point Raises the temperature
about causing and stoking trans panic . And we haven’t really seen that
Softens what happened: pushback 2 points Softens what happened
is a call for a pushback against ICE. But I don’t think

Layer scores

Rates are counted points per 1,000 words of the story's own text. For a story longer than 200 words, the rate used is the average of the whole-story rate and the rate in its densest 200-word stretch, so neutral filler cannot dilute a loaded passage away. Score = 100 × (loaded end − rate used) ÷ loaded end, kept between 0 and 100. Headline words count only in the headline layer.

Layer	Points	Words	Whole-story rate	Densest 200 words	Rate used	Scale	Score
Word choice	7	1732	4.0	15.0 (words 1051 to 1250)	9.5	0 to 40	76
Temperature	6	1732	3.5	10.0 (words 801 to 1000)	6.7	0 to 40	83
Flagged attribution phrases	0	1732	0.0	0.0 (words 1 to 200)	0.0	0 to 20	100
Headline wording	0	25	0.0	headline only	0.0	0 to 240	100

Densest stretch: Word choice, words 1051 to 1250 of 1732, with actually, clearly; Temperature, words 801 to 1000 of 1732, with huge, panic.

Shown, not scored: the headline's rate minus the rate of the story's first 80 words is 0.0 points per 1,000 words.

Overall

Weighted geometric mean of the layers that are established, with 10 added to each layer first and taken away at the end: (Word choice 76 + 10)^0.4 × (Temperature 83 + 10)^0.3 × (Flagged attribution phrases 100 + 10)^0.2 × (Headline wording 100 + 10)^0.1 − 10 = 85. Adding 10 means one layer at 0 lowers the total steeply without collapsing it. A weak layer pulls the total down.

Lowered the score most: Word choice.

Name-swap test: with party, politician and institution names swapped, this report's score moves by 0.0 points.

What a reader could check

People named as sources	0
Unnamed sources	0
Links to primary records (government, court, filings, PDFs)	0
Documents cited in the text (a report, bill, ruling, filing)	0
Checkable specifics (numbers and dates)	9
Data shown (a table or chart)	no
Correction or clarification noted	no

What a reader could check, counted by published patterns. Shown beside the score, never part of it. How each count works

Checked against the official record

No vote count or bill number found in the text read.

Record of this measurement

Method 3.1.0, word-list fingerprint 807a17189402a416, read Wed, Nov 4, 3:11 PM ET by text extractor version 4. Fingerprint of the text read: c2f7307cc69b54ac. Internet Archive copy nearest the time it was read. The text read was not kept (read before method 3.1.0, or from the feed only), so a later rule change can be applied only while the report is still in the outlet's feed.

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The arithmetic for one report