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In English, mass nouns are characterized by the impossibility of being directly modified by a numeral without specifying a unit of measurement and by the impossibility of being combined with an indefinite article (a or an). Thus, the mass noun "water" is quantified as "20 litres of water" while the count noun "chair" is quantified as "20 chairs".
The idea of the "universal grinder" is that, while count nouns usually denote whole, distinct objects (such as a steak, two steaks), the equivalent mass noun connotes a non-distinct quantity of whatever constitutes these objects (some steak). The universal grinder suggests that most count nouns can be used as mass nouns, when the distinct thing ...
The concept of a "mass noun" is a grammatical concept and is not based on the innate nature of the object to which that noun refers. For example, "seven chairs" and "some furniture" could refer to exactly the same objects, with "seven chairs" referring to them as a collection of individual objects but with "some furniture" referring to them as a single undifferentiated unit.
In Kiowa, by default, Class I nouns are singular-dual, Class II nouns are plural (two or more), Class III nouns are dual, and Class IV nouns are mass nouns with no number. The inverse number marker changes the noun to whatever number(s) the unmarked noun isn't, such as changing Class III nouns from dual to nondual. [ 277 ]
A bare noun is a noun that is used without a surface determiner or quantifier. [1] In natural languages , the distribution of bare nouns is subject to various language-specific constraints. Under the DP hypothesis a noun in an argument position must have a determiner or quantifier that introduces the noun, warranting special treatment of the ...
The words you and we share features commonly associated with both determiners and pronouns in constructions such as we teachers do not get paid enough. On the one hand, the phrase-initial position of these words is a characteristic they share with determiners (compare the teachers).
[90] [91] [92] [3] Reviews of early ITS systems (1995) showed an effect size of d = 1.0 in comparison to no tutoring, where as human tutors were given an effect size of d = 2.0. [90] Kurt VanLehn's much more recent overview (2011) of modern ITS found that there was no statistical difference in effect size between expert one-on-one human tutors ...
1 · 2 = 1 + 1, and 2 · 2 = 2 + 2, and 3 · 2 = 3 + 3, ..., and 100 · 2 = 100 + 100, and ..., etc. This has the appearance of an infinite conjunction of propositions. From the point of view of formal languages , this is immediately a problem, since syntax rules are expected to generate finite words.