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Comment by spxdcz | Hacker News Reader

I'm not convinced the "evidence" is suggesting anything without further data, and this article is glossing over "correlation != causation". Without a baseline (a situation where, over the same years, tuition fees weren't introduced/raised), how do we know what the equivalent situation would be? Perhaps there would have been even more people from poorer backgrounds applying.

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It is evidence. No need to put it in scare quotes. We can debate the correct interpretation and applicability, but it's certainly evidence of a sort.

It's impossible to run the kinds of controlled large scale socio-economic experiments you describe. If we ignore the evidence that doesn't meet your high standards, we'll have no real world data.

Recently it was discovered that working 20 hours a week while going to school results in worse grades - after decades of believing the exact opposite. When they did better studies - comparing like students (same school, same background, and other characteristics), they discovered that all the prior studies were just showing the success of students who really should have been even more successful. So I prefer to think of most studies such as this as a datapoint, rather than any type of evidence.

A datapoint is evidence, just not proof.

You might want to look up the definition of evidence. My reading of three definitions just doesn't quite match your definition. But no big deal. I think we agree, and this has become about word interpretation.

It's better to recognize the lack of good data and the limits of our knowledge than to come to incorrect conclusions.

There's things you know, things you don't know, and things you think you know but you don't know. It's the last one that harms the most.

Sooo... What's the actionable decision here?

    > If we ignore the evidence that doesn't meet your high
    > standards, we'll have no real world data.

I would also add that variable standards of evidence are a good way to allow your strongly cherished beliefs to remain unchallenged for a long time.

* No comparison with other time periods, and their respective tuition fees.

* No comparison with other countries, and their respective policies.

* No data on where these students graduate from, or in which subjects, or with which grades, or what their average salary is X years later, or whether they'll actually be able to pay back the loan.

It's missing a huge amount of important information; you really can't justify the conclusion "tuition fees are good" from this alone.

I don't think the claim is "tuition fees are good," but that reducing them may not be the best use of the allocated money.

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