Expertise, Relevance and Types of Knowledge

Abstract

In this paper, we argue that the formulation of typical expert judgementshere referred to as 'judgement calls'entails figuring out how to apply 'general knowledge' to specific circumstances (what we call the 'relevance query'). This requires wisdom, in its original Aristotelian sense, on the part of the scientific expert, as knowledge of laws and initial conditions is not sufficient to make judgement calls. Experts need to take into consideration factors coming from 'outside' the remit of scientific theory, thereby crossing the divide between empirical evidence and socio-political input (what we call the 'expert query'). Arguing against some form of the fact-value distinction is far from an original move, but we will do so both by avoiding the conclusion that expert judgements are nothing but political (against the received view in the sociology of science), and by advocating a somewhat novel perspective. We will claim that expert scientific knowledge proves to be inadequate when it is not integrated with local knowledge, which we define as the knowledge of all factors, which are deemed relevant to the application of general knowledge to specific circumstances. The possession and role of this type of knowledge, though partly an empirical (or sociologically situated) question, can be justified by epistemological reasons.

Qualitative modelling of social determinants of health using group model building: the case of debt, poverty, and health

“…Their type of knowledge can therefore be regarded as having similarities to both of the other types of evidence, while being different. Utilising these three types of information, each with a different purpose and value, offers a more nuanced view than only one or even two of them would have [ 47 , 48 ].…”

Objectivity and Intellectual Humility in Scientific Research: They’re Harder Than You Think

“…The third problem was highlighted by Montuschi in a paper with Pierluigi Barrotta (2018b), ‘Expertise, relevance and types of knowledge’. Here, Montuschi and Barrotta argue that there was too much reliance on general knowledge and too little attention to local knowledge.…”

Modeling Expertise Through Decision-based Learning: Theory, Practice, and Technology Applications

“…Conceptual knowledge has also been referred to as declarative knowledge (Sugiharto et al, 2018;Tofel-Grehl & Feldon, 2013); although Anderson et al (2001) argued that the term conceptual knowledge is preferred when referencing larger ideas, theories, models, etc., while declarative knowledge should refer to "discrete, isolated content elements (i.e., terms and facts)" (p. 41). Conceptual knowledge develops a foundation of theoretical understanding within a discipline that helps students understand a wide array of problems (Alamäki, 2018;Barrotta & Montuschi, 2018;Greca & Moreira, 2000). For example, an architect knows what to look for in a high-quality design because he/she knows the guiding concepts of what to look for, such as stability of materials, foundational strength, and weathering patterns.…”

“…Not only do they have knowledge of concepts and procedures, but they also understand the conditions under which to apply that knowledge (Amolloh et al, 2018;Elvira et al, 2017;Lorch, Lorch, & Klusewitz, 1993). As Barrotta and Montuschi (2018) put it, experts have "knowledge of the specific relevant circumstances to which [theory] is applied" (p. 390). Experts are skilled at decision-making under novel situations because they recognize conditional patterns and can focus on productive strategies (Elvira et al, 2017;Ivarsson, 2017;Johnson, 2005;Oluwatayo et al, 2017) Where novices are swimming in a sea of surface features, experts cut through to the conditions that are salient and essential (Le Maistre, 1998;Swan et al, 2020;Van de Wiel, 2017).…”