The arithmetic for one report
Opposition to AI data centers in the midterms foreshadows tougher regulations ahead
95Few flagged expressions Wire copy: shown here but left out of the outlet's own score.
What was read
1070 words in the outlet's own voice, plus 12 in the headline. 10% of the text is in quotes. 27 attribution markers (such as "said" or "according to") found.
Words found
- Raises the temperature:
outrage
2 points Raises the temperature
a campaign season filled with outrage against artificial intelligence data centers, thesweeping
1 point Raises the temperature
a more than 3-to-1 ratio. Sweeping wins by Democrats could have far-reaching
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 | 0 | 1070 | 0.0 | 0.0 (words 1 to 200) | 0.0 | 0 to 40 | 100 |
| Temperature | 3 | 1070 | 2.8 | 10.0 (words 1 to 200) | 6.4 | 0 to 40 | 84 |
| Flagged attribution phrases | 0 | 1070 | 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: Temperature, words 1 to 200 of 1070, with outrage
.
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 100 + 10)0.4 × (Temperature 84 + 10)0.3 × (Flagged attribution phrases 100 + 10)0.2 × (Headline wording 100 + 10)0.1 − 10 = 95. 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: Temperature.
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 | 4 (Clayton Tucker, Data Center Watch, Morgan Stanley, Stephen Sanders) |
|---|---|
| Unnamed sources | 0 (0% of all sources found) |
| Links to primary records (government, court, filings, PDFs) | 0 |
| Documents cited in the text (a report, bill, ruling, filing) | 2 |
| Checkable specifics (numbers and dates) | 15 |
| 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 by text extractor version 4. Fingerprint of the text read: 45ede928e6af5d51. 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.