It is no longer merely the vogue to ignore common sense, but now only sufficient to jettison the concept altogether.
I don’t know, there must be some other world that people are talking about when they make certain claims about things which fly in the face of the most commonly repeatable observations.
All I know, is that I must not be living in that world.
There are two phrases I hear from so-called ‘cultured Americans’ all the time:
1) ‘You never know.’
2) ‘Correlation does not equal causality.’
These are the two darling favorites among intellectuals today, though I hear them all the time in ‘mainstream’ society as well.
Abstract studies, mostly the realms of Psychology, Sociology, Philosophy, Economics, etc., that is, the so-called ‘humanities,’ must be studied mostly through repeatable patterning by independent correlation.
This is to be contrasted from the ‘hard’ or so-called ‘positive’ sciences such as Physics, Chemistry or Math, which operate on empiric direct causality more than they do correlation.
Though, true, correlation does not equal causality, it is also true that ‘correlation can mean a probability for causation.’ In other words, there are many instances in which a correlation denotes probability for a cause, often great probability.
It is this probability subjectivism and its consequent ‘new vogue’ have thrown out the window, and it is this probability that is the basis of common sense.
I wait tables, which gives me a curious vantage point to observe such probability in a realm, –public human behavior– where so many daily correlations can be made, many of which contradict ‘our’ politically correct sensibilities.
What I find is that most of the so-called stereotypical patterns are actually pretty dead on, when one has the courage in the face of the PC culture, to uphold common sense.
But what do I mean by ‘common sense,’ if so many define it in so many different ways?
I define common sense as a modification from its original definition. Common sense, colloquially understood, runs something along the lines of: ‘An understanding common to most reasonable and rational individuals.’
My definition comes from the vantage point of a more objective concept, since I believe the colloquial one to be susceptible to a greater number of contradictions. Common sense here, is: ‘that which is derivable from actually observed human experience (directly or indirectly), as relative to a level of trust limited by the pragmatics of a reasonable, common individual–as qualified by probability in relation to predictable results and delimited as relative to a corresponding given setting.’
The first distinguishing characteristic of this idea of common sense, of course is ‘practically limited and defined trust from probability.’ This means that if knowing something is for any reason, whether it be too broad and complex, intangible, etc., and hence, impractical to study and still be accurate–it falls outside the realm of mere common sense and must be considered by actual scientific research.
To further explain the definition, note that the above ‘practically limited probability’ is contingent upon a few qualifiers: First, I keep the qualifier of ‘accurate predictable results’ since the commonly held notion of common sense implies rationality by necessity, and is in any case further illustrated by the reference I make to a ‘reasonable individual.’ The word ‘common’ has a very important role to the idea as well: it does not mean a ‘common individual’ culturally though, since that would be subjective. ‘Common’ here means that which is reasonable to believe, is common to all individuals present within the setting (‘…as delimited by a correspondingly given setting..’) where data has been observed, as a necessary consequence of being present in such a setting.
This is not to say that science shouldn’t check and be the ultimate resource on the best provisional truth of all things. However, science should NOT be used as grounds or a tool to stamp out provisional conclusions which are not tested through an actual, precise, verified, completely controlled scientific study.
There is something tricky here though, to this idea that one must be careful with: it is not necessarily impractical to have an accurate predictability about something that appears and in actuality, very well could be vastly complex–such is the crux of my entire point, in fact. This is because complexity does not rule out practicality, depending on the nature of the phenomena, and is why I have chosen human individual practicality over sheer complexity as the key idea of my definition of common sense.
Notions such as the theory of evolution fall into this category. Darwinist evolutionary theory, for example, is plausibly conceivable to be based entirely from common sense alone and actually be predictable. It is entirely possible, without scientific testing to observe the patterns evolution produces, since they are inherent in everything living.
So I would say that one must draw the line between common sense and science with the fact that science is far better and ultimately more accurate than common sense, but both should be considered in correlation with each other as a total-view convergence of cross-referenced data.
That is why the trust we derive from cross-referencing our directly observable experiences as well as cultural probabilities i.e. that modern medicine is not a farce, or that man did in fact, land on the moon–must be integrated with, not segregated from, our more abstract research and theory, i.e. general study of existing knowledge as well as serious scientific testing.
Together both are intended to produce a ‘convergence of evidence’ through which we develop our most abstract and broadest idea of the world and reality. But instead of creating this kind of intellectual harmony, the subjectivist culture, especially among the intelligentsia, prefer to treat the two with completely different standards.
Trust as opposed to faith, relies on probability from a given body of evidence. faith does so, on no evidence whatsoever. Science, contrary to how most seem to view it, also relies on a level of trust, albeit a far lower level. Nevertheless, trust is still a component of science since all science deals with probability, claiming only provisional conclusions, even unto itself.
I hear from my restaurant co-workers all the time such phrases as ‘well you never know how business is going to be,’ or ‘you never know how a given person will tip.’
At the very same time, we all cringe when we see the typical set of characteristics to an individual we know there is a great probability will not tip.
Here is a list I have generated which is or should be at least the implicit crib sheet of restaurant-waiter probabilities.
Consider that this is based off of -potentially- very sound common sense, since these are observations that hold so much repeatability and are common to anyone inside this setting. Though I should mention that some of these observations are very, very surprising to most and to such opinions, could never qualify as common sense:
1) A person eating alone is far more likely to tip far less, since he or she has a limited bill, and in fact, we can conclude that the lower the bill, perhaps more than 90% of the time, means the lower the tip. (Keep in mind that that percentage is probably extremely generous to my opposing argument.)
2) Black people don’t generally tip very well, though a certain small percentage may, and depending on the demographic, will tip higher, but mainly still less than other ‘races’–i.e. I have observed that even most black guests who have characteristics that suggest a high level of probability that they make much more than I do, still tip less.
(To attempt to avoid being called a racist, –which I am NOT–, I assume this is racially cultural, not necessarily genetic.)
3) Low class Caucasian or white people also don’t tip very well, though more white people than black will tip better on a whole.
4) Politeness in guests does not usually equal a better tip, although there is slightly higher a probability that they will.
5) Well dressed people, meaning those wearing garments of obvious cost, of any degree higher than the usual, usually means a better tip.
6) Families as well as parties with children tip less than single people in groups with exception to teenagers, of whom, are at extremely high risk to tip next to nothing.
7) The ideal age-demographic for a table is probably 20-35, and the ideal number at a table is 2-6, since tables can be turned quicker with fewer numbers and smaller numbers of people are easier to deal with.
8) Couples are extremely more likely to buy a bottle of wine.
9) ‘Four-Tops’ or groups of four are the juggernaut of good tips, that can be turned quickly.
10) Articulate and well spoken guests who are suggestively from a higher educational level and background, possess a much greater probability that at least a modestly better tip will result.
11) Drinkers and smokers tip well, period, though the former more than the latter.
12) Political conversation esp. at bars, BARS good tips. Talking politics at tables or bars, is notoriously divisive and a big ‘no-no’ among bartenders and waiters alike.
To be Continued Tomorrow in Part II…