Logical theory revision through data underdetermination: an anti-exceptionalist exercise

The anti-exceptionalist debate brought into play the problem of what are the relevant data for logical theories and how such data affects the validities accepted by a logical theory. In the present paper, I depart from Laudan's reticulated model of science to analyze one aspect of this problem, namely of the role of logical data within the process of revision of logical theories. For this, I argue that the ubiquitous nature of logical data is responsible for the proliferation of several distinct methodologies for logical theories. The resulting picture is coherent with the Laudanean view that agreement and disagreement between scientific theories take place at different levels. From this perspective, one is able to articulate other kinds of divergence that considers not only the inferential aspects of a given logical theory, but also the epistemic aims and the methodological choices that drive its development.

On the metaphysics of (epistemological) logical anti-exceptionalism

A recent logical anti-exceptionalist trend proposes that logical theories are revisable in the same manner as scientific theories, either on grounds of the method of theory selection or on what counts as evidence for this revision. Given this approximation of logic and science, the present essay analyzes the commitments of both these varieties and argues that, as it currently stands, this kind of anti-exceptionalism is committed to scientific realism, that is, to realism about some unobservable entities evoked in logical theories. The essay argues that anti-exceptionalism cannot be separated into metaphysical and epistemological varieties, and proposed rather to label anti-exceptionalists views either broadly in terms of theory revision, or narrowly in terms of logic’s affinity with science.

Transfer Learning by Mapping and Revising Boosted Relational Dependency Networks

Statistical machine learning algorithms usually assume that there is considerably-size data to train the models. However, they would fail in addressing domains where data is difficult or expensive to obtain. Transfer learning has emerged to address this problem of learning from scarce data by relying on a model learned in a source domain where data is easy to obtain to be a starting point for the target domain. On the other hand, real-world data contains objects and their relations, usually gathered from noisy environment. Finding patterns through such uncertain relational data has been the focus of the Statistical Relational Learning (SRL) area. Thus, to address domains with scarce, relational, and uncertain data, in this paper, we propose TreeBoostler, an algorithm that transfers the SRL state-of-the-art Boosted Relational Dependency Networks learned in a source domain to the target domain. TreeBoostler first finds a mapping between pairs of predicates to accommodate the additive trees into the target vocabulary. After, it employs two theory revision operators devised to handle incorrect relational regression trees aiming at improving the performance of the mapped trees. In the experiments presented in this paper, TreeBoostler has successfully transferred knowledge among several distinct domains. Moreover, it performs comparably or better than learning from scratch methods in terms of accuracy and outperforms a transfer learning approach in terms of accuracy and runtime.

Interrogating culture: Anthropology, social work, and the concept trade

Summary Interdisciplinary contributions to social work have supported the profession’s development as a helping profession. Indeed, drawing from other disciplines has been a way to hone intervention approaches. This article analyzes the history of social work’s use of anthropological theory about “culture” in order to critically examine the profession’s positioning as a “recipient” of theories. At a time when evidence-based practice is a dominant ideal, this paper offers an opportunity to step back and interrogate a key concept, culture, that is often evoked as interventions are tailored for various populations. Findings While social work has substantially debated and revised how it approaches culture difference, the core conceptualization of culture as a relatively static set of shared values and traits remains ill-suited to the complex negotiation of diversity in social work practice. The limitations of the culture concept are symptomatic of an exchange relationship with anthropology that positions social work practitioners primarily as recipients of concepts, rather than as interlocutors. Application By treating intervention as an opportunity for theory revision, anthropologists and social workers can better account for the hybridity, change, and contestation of difference in social work practice. As the social work profession expands globally, a more dialogical engagement with anthropological theories about culture and other key concepts may prove fruitful.