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Class (philosophy)

About: Class (philosophy) is a research topic. Over the lifetime, 821 publications have been published within this topic receiving 28000 citations.


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Journal ArticleDOI
TL;DR: In this article, the authors focus on the particular kind of labels or abstractions which arise in development policy areas as an aspect of the donative political discorse associated with the 3rd world development agenda.
Abstract: Labelling a feature of all social communication is an aspect of public policy (utterance and practice) an element in the structure of political discourse. Contributors to this volume have become more sharply aware of this through their preoccupation and experience with development issues in various parts of the 3rd world. The purpose of this focus on labelling is to reveal processes of control regulation and management which are largely unrecognized even by the actors themselves. The significance of labelling has been underestimated as an aspect of policy discourse and especially for its structural impact upon the institutions and their ideologies through which people are managed. Since the process of labelling affects the categories within people are socialized to act and think the object of this concern is fundamental rather than peripheral. Labelling refers to a relationship of power in that the labels of some are more easily imposed on people and situations than those of others. Focus here is on the particular kind of labels or abstractions which arise in development policy areas as an aspect of the donative political discorse associated with the 3rd world development agenda. The interest is in how specific acts of designation or classification reflecting specific interests become universalized. It is not sufficient to say that concept of the state (as an endorsement or imposition of legitimate public actions) is "a condensate of class relations" or is "derived from thelogic of capitalist production relations" "a particular from because of the contradictions of its peripherality." It is necessary to understand how this endorsement actually occurs and can continue to do so how it comes to be constructed and then persists. The process is insidious and centrally involves "labelling." Labelling is the attribute of a certain kind of public management of resources i.e. bureaucratic professional formal institutionalized and often central. It is the counterpart of access in that the authors of labels of designations have determined the rules of access in that particular resources and privileges. A central feature of the labelling proces is the differentiation and disaggregation of the individual and the individuals subsequent identification with a principal label e.g. "landless" or "single parent." Labelling refers to the weighting applied the differentiated elements. "Problems" calling for attention and policy are constructed and defined in this way leading to 1 label or element representing the entire situation of an individual family. Exercises required in an attempt to demcratize the "which" and "whose" aspects of public policy labelling are identified.

131 citations

01 Jan 2000
TL;DR: This application shows some of the weaknesses of the SVDD, particularly the dependence on the scaling of the features, by rescaling features and combining several descriptions oll well scaled feature sets, performance can be significantly improved.
Abstract: In previous research the Support Vector Data Description is proposed to solve the problem of One-Class classification. In One-Class classification one set of data, called the target set, has to be distinguished from the rest of the feature space. This description should be constructed such that objects not originating from the target set, by definition the outlier class, are not accepted by the data description. In this paper the Support Vector Data Description is applied to the problem of image database retrieval. The user selects an example image region as target class and resembling images from a database should be retrieved. This application shows some of the weaknesses of the SVDD, particularly the dependence on the scaling of the features. By rescaling features and combining several descriptions oll well scaled feature sets, performance can be significantly improved.

131 citations

Journal Article
TL;DR: The process of formal definition in advanced mathematics actually consists of two distinct complementary processes: the first is the abstraction of specific properties of one or more mathematical objects to form the basis of the definition of the new abstract mathematical object and the second is the process of construction of the abstract concept through logical deduction from the definition as discussed by the authors.
Abstract: ion An abstraction process occurs when the subject focuses attention on specific properties of a given object and then considers these properties in isolation from the original This might be done, for example, to understand the essence of a certain phenomenon, perhaps later to be able to apply the same theory in other cases to which it applies Such application of an abstract theory would be a case of reconstructive generalization – because the abstracted properties are reconstructions of the original properties, now applied to a broader General, Abstract and Generic Guershon Harel & David Tall – 4 – domain However, note that once the reconstructive generalization has occurred, it may then be possible to extend the range of examples to which the arguments apply through the simpler process of expansive generalization For instance, when the group properties are extracted from various contexts to give the axioms for a group, this must be followed by the reconstruction of other properties (such as uniqueness of identity and of inverses) from the axioms This leads to the construction of an abstract group concept which is a re-constructive generalization of various familiar examples of groups When this abstract construction has been made, further applications of group theory to other contexts (usually performed by specialization from the abstract concept) are now expansive generalizations of the original ideas The case of definition The process of formal definition in advanced mathematics actually consists of two distinct complementary processes One is the abstraction of specific properties of one or more mathematical objects to form the basis of the definition of the new abstract mathematical object The other is the process of construction of the abstract concept through logical deduction from the definition The first of these processes we will call formal abstraction, in that it abstracts the form of the new concept through the selection of generative properties of one or more specific situations; for example, abstracting the vector-space axioms from the space of directed-line segments alone or from what it is noticed to be common to this space and the space of polynomials This formal abstraction historically took many generations, but is now a preferred method of progress in building mathematical theories The student rarely sees this part of the process Instead (s)he is presented with the definition in terms of carefully selected properties as a fait accomplit When presented with the definition, the student is faced with the naming of the concept and the statement of a small number of properties or axioms But the definition is more than a naming It is the selection of generative properties suitable for deductive construction of the abstract concept The abstract concept which satisfies only those properties that may be deduced from the definition and no others requires a massive reconstruction Its construction is guided by the properties which hold in the original mathematical concepts from which it was abstracted, but judgement of the truth of these properties must be suspended until they are deduced from the definition For the novice this is liable to cause great confusion at the time The newly constructed abstract object will then generalize the General, Abstract and Generic Guershon Harel & David Tall – 5 – properties embodied in the definition, because any properties that may be deduced from them will be part of it Because of the difficulties involved in the construction process, this is a reconstructive generalization Occasionally the process leads to a newly constructed abstract object whose properties apply only to the original domain, and not to a more general domain For instance, the formal abstraction of the notion of a complete ordered field from the real numbers, or the abstraction of the group concept from groups of transformations Up to isomorphism there is only one complete ordered field, and Cayley’s theorem shows that every abstract group is isomorphic to a group of transformations In these cases the process leads to an abstract concept which does not extend the class of possible embodiments We include these instances within the same theoretical framework for, though they fail to generalize the notion to a broader class of examples, they very much change the nature of the concept in question The formal abstraction process coupled with the construction of the formal concept, when achieved, leads to a mental object that is easier for the expert to manipulate mentally because the precise properties of the concept have been abstracted and can lead to precise general proofs based on these properties Formal abstraction leading to mathematical definitions usually serves two purposes which are particularly attractive to the expert mathematician: (a) Any arguments valid for the abstracted properties apply to all other instances where the abstracted properties hold, so (provided that there are other instances) the arguments are more general (b) Once the abstraction is made, by concentrating on the abstracted properties and ignoring all others, the abstraction should involve less cognitive strain These two factors make a formal abstraction a powerful tool for the expert yet – because of the cognitive reconstruction involved – they may cause great difficulty for the learner

129 citations

Patent
17 Mar 1995
TL;DR: In this article, a method of computer aided design of geometric models including the steps of defining a set of geometric entities for use in constructing the geometric models, each of the geometric entities being an abstract geometric object type that is adapted to be actualized into one or more geometric objects, identifying some geometric objects by corresponding unique object identifiers, defining a plurality of relational entities along the set of geometrically defined entities.
Abstract: A method of computer aided design of geometric models including the steps of: defining a set of geometric entities for use in constructing the geometric models, each of the geometric entities being an abstract geometric object type that is adapted to be actualized into one or more geometric objects, the geometric entities including point class entities, curve class entities, and surface class entities; identifying some of the geometric objects by corresponding unique object identifiers; defining a plurality of relational entities along the set of geometric entities, each of which is adapted to be actualized into corresponding relational objects having having a dependency relationship upon one or more other geometric objects whose object identifiers are specified within the relational objects; wherein the relational entities include a curve class entity having a dependency relationship on a point class object; wherein at least one of the relational entities is a surface class entity having a dependency relationship on a point class object or a curve class object; and defining a set of subroutines for evaluating the plurality of geometric objects, there being a corresponding subroutine for each of the abstract geometric object types, wherein those subroutines which evaluate relational objects are programmed to make calls to an appropriate one or more subroutines to evaluate the geometric objects on which that relational object depends.

126 citations

Journal ArticleDOI
TL;DR: Evidence is presented that, developmentally, this bias precedes learning to count and it is proposed that this discrete physical object bias facilitates mastery of counting.

121 citations


Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20241
202311,771
202223,753
2021380
2020186
201962