|Problems? Is your data what you think it is?|
Re^4: If you believe in Lists in Scalar Context, Clap your Handsby BrowserUk (Pope)
|on Oct 28, 2008 at 07:42 UTC||Need Help??|
That's the obvious answer.
Outside of women's fashion, I don't see much wrong with the obvious :)
Beyond the obvious, because a simpler story makes for easier learning.
For the proof of that, you'd have to read the quotes, and preferably the whole chapter they were drawn from. He makes the case better than I ever could. In particular, see the "French air-traffic controller" example to see how the ridged application of correctness can take a disastrous toll on productivity.
The 'no such thing' model just doesn't stand up to either the novice users hands-on perceptions: print scalar ('a','b','c');, even if that perception were technically flawed--which by your own testimony it isn't--or the reality.
If you're going to go with a known-flawed model, then go with one that fits the users perceptions, and allow them to become aware of and compensate for it's imperfections, as the need arises. Rather than a model that contradicts their perceptions, and requires them to make a huge leap of (either acquired or actual), knowledge, in order to become comfortable with it. Especially as they will have to unlearn either at some future point.
Examine what is said, not who speaks -- Silence betokens consent -- Love the truth but pardon error.
"Science is about questioning the status quo. Questioning authority".
In the absence of evidence, opinion is indistinguishable from prejudice.