In the Youtube Downloader search, NortonSafeWeb is nowhere to be found. I get a couple of legit downloader websites, and some articles from reputable tech newspapers on how to use them or command line tools.
In the Adblock search, ublock Origin is #3, followed by some blogs about ad blocking ethics debates and the bullshit Google has been pulling recently.
In the wider tires grip search, #3 is a physics blog that dives deep into the topic.
In the transistors search, the first reddit link directly answers the question in very similar wording to the hypothetical correct answer spelled out in the rubric. 4/5 of the reddit results are on the correct topic, followed by two SuperUser questinos also on the correct topic, then some linus tech tips and toms hardware articles, also on the correct topic. No Quora questions.
In the vancouver winter snow search, the first several results are from local news papers talking about the anticipated effects of el nino on snowfall, and then a couple of high-quality blogs and weather sites.
Really wondering how Dan got such bad results.
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Aside from that, the way that the author expects all the results to return the same kind of thing is just... weird? Like, that's not how search engines are supposed to work. A search that gives you 10 links to fundamentally the same thing is a bad search. Search results should cover a breadth of reasonable guesses for what you should be looking for given a query. If you search for "download firefox", and you scroll past the first 5 download links, then you're probably not actually looking for a download link and a blog post about firefox is not "irrelevant" and shouldn't be points against.
This opinion is even borne out in search engine quality metrics that have been industry-standard for decades, like mean reciprocal rank and distributed cumulative gain. What matters is how far you have to scroll to get to a good result, not what proportion of the first N results are good.