ideas proposed by each of the four major schools of thought and focuses particularly on their philosophical assump-tions concerning the nature of science and their approach to theorising about educational administration.

It is now widely accepted that Research & Development in nanotechnology and biotechnology should be accompanied by research programs in ethics. This paper first critically assesses the ini-tiatives that characterize this “ethical turn ” by clarifying its underlying philosophical assump-tions

related disciplines as well. Even where underlying philosophical assump-tions influence their thinking and writing, students of practical reasoning often fail to acknowledge these influences. That is a great pity. By looking to epistemology, a richer and more coherent development of practical reasoning

Transactional analysis and adult educa-tion are both located within the tradition of humanistic psychology,and they share many underlying assumptions, including that hu-man beings naturally tend toward growth and change, that adults are responsible for themselves, and that people are inherently

with, theoretical, epistemological and ontological assumptions – including concep-tions of subjects and subjectivities, and understandings of how knowledge is con-structed and produced. In suggesting how epistemological and ontological positionings can be translated into research practice, our article

kind of naiveté concerning knowledge claims. The opposite of realism may be termed antirealism, idealism, or nominalism. Although many people confuse empiricism and positivism with realism, these tradi-tions are by nature strongly antirealist, which is why a sharp distinction should be made between

Two of the predominant approaches to gaining knowledge in the social sciences are the positivist and interpretive approaches. Different philosophical assumptions and goals underlie both. We are better able to see the strengths and weaknesses in the two approaches by comparing and contrasting

of a global climate model using distinct data sets considered col-lectively will provide stronger evidence for a model than either one of the instances considered individually. This has consequences for model ro-bustness. Sets of models that produce robust results will, if their assump-tions vary

-less of whether these are determined in light of a set of background assump-tions. Moreover, the putative literal meanings of sentences da not contribute in systematic ways toward the understanding of speakers ’ utterance mean-ings. These observations suggest that the distinctions between literal and metopharic

In their attempt to model and reason about the beliefs of agents, artificial intelligence (AI) researchers have borrowed from two different philosophical tradi-tions regarding the folk psychology of belief. In one tradition, belief is a relation between an agent and a proposition, that is, a