User:Blast Ulna

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This user is a member of the

Association of Wikipedians Who Dislike Making Broad Judgments About the Worthiness of a General Category of Article, and Who Are in Favor of the Deletion of Some Particularly Bad Articles, but That Doesn't Mean They Are Deletionists

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Est omnino difficile iudicare inclusionis meritum cuiusdam rei in encyclopædia cum ratio sciendi quid populi referat incerta sit, sed nihilominus aliquid encyclopædiam dedecet

It is generally difficult to judge the worthiness of a particular topic for inclusion in an encyclopedia considering that there is no certain way to know what interests people, but some topics nevertheless are not fit for an encyclopedia.

This motto reflects the desire of these Wikipedians to be reluctant, but not entirely unwilling, to remove articles from Wikipedia.

The classical exposition of the scientific, or inductive method (originally due to William of Occam) is what is now called Mill’s Canons, the two most important of which are:

  • The Canon of Agreement which states that whatever there is in common between the antecedent conditions of a phenomenon can be supposed to be the cause, or related to the cause, of the phenomenon.
  • The Canon of Difference which states that the differences in the conditions under which an effect occurs and those under which it does not must be the cause or related to the cause of that effect.

In addition, the method relies upon the Principle of Accumulation which states that scientific knowledge grows additively by the discovery of independent laws, and the Principle of Instance Confirmation, that the degree of belief in the truth of a law is proportional to the number of favourable instances of the law. To the methods of inductive reasoning we should add considerations of plausibility of mechanism. Science is also unique in the area of philosophy since theories may be experimentally falsified. It only requires one firm observation which cannot be predicted or explained in the accepted scientific model of a phenomenon to falsify this model.