The phrase "a fixed category" is correct and usable in written English.
It can be used to describe a classification or grouping that does not change or is stable over time.
Example: "In our research, we found that the subjects fell into a fixed category based on their responses."
Alternatives: "a stable classification" or "a defined group".
Yet most gay historians resist any depiction of homosexuality as a fixed category transcending time.
The idea that there is a middle ground -- that gender is not a fixed category, but a fluid domain of expression and experimentation -- has been a staple of academic discourse for some time.
But, he added, "rather than conclude that zeitgeist is a fixed category that we used to have more of and now we have less of, I'd say that the zeitgeist of zeitgeist is changing".
Not until the nineteenth century did doctors and lawmakers commonly acknowledge a fixed category called sexual "inversion," and not until the twentieth century did the United States see "widespread discrimination against a class of people on the basis of their homosexual status".
This is in part due to the disagreement with the 'traditional' concept of ethnic enclave understood as a fixed category focused on spatial concentration.
The bias typically associated with animal threshold models should not be confused with general extreme-category problems (when all observations within a fixed category belong to one of the binary classes), as the latter may cause bias for threshold models in general.
Is it that we tend to define real jobs in a certain fixed category?
Naturally, for a given subscale with fixed category intercepts, it becomes possible to display bias in relation to different levels of μ ERS as a function of μ ENV to better illustrate how between-country variability in response style will introduce bias in the mean scale score estimate of ENV for that country.
The objective of scene-level labeling is to assign each superpixel i a category label l i from fixed category label set L. The energy E(L) of our MRF model over all superpixels is defined as follows: E(L =sum_{i}psi(l_{i})+lambda_{Phi}sum_{ i,j }phi_{ij}(l_{i}, l_{j}), (1).
We would, in future, attempt to keep fixed category responses to an absolute minimum and to limit the number of "other" options available.
The interpretation of higher estimated probabilities for 'no fixed' attributes at zero, corresponding to reduced likelihood of employing heuristics, is supported by a relatively higher proportion of literate respondents grouped in the 'no fixed' category.
