Islam, indigeneity, and religious difference in a secular context: Canadian case studies

This paper analyzes the hardening religious difference in contemporary Canadian society and explains why the presence of Muslims, including new converts, constantly incites in the public imagination the primordial threat of Islam to the secular accomplishments of Canadian society. Relying on the available data and previous research on the historical formation of the secular in Canada, the author attempts to detect a paradox within the state-lead politics of recognition that unintentionally creates the conditions for new communal conflicts” (warna kuning) diubah menjadi “Relying on the available data and previous research on the historical formation of the secular in Canada, the author attempts to detect a paradox within the statelead politics of recognition that unintentionally creates the conditions for new communal conflicts. By using an inductive generalization, the author argues that the perceived incompatibility between Islam and secular values is derived not so much from cultural and theological differences or actual political threats posed by Muslims or Indigenous converts. It instead emanates from the self-understanding of the majority of Canadians that defined the nation as essentially Christians and simultaneously secular.

First Wave Feminism: Craftswomen in Plato’s Republic

Ancient Athenian women worked in industries ranging from woolworking and food sales to metalworking and medicine; Socrates’ mother was a midwife. The argument for the inclusion of women in the guardian class must be read in light of this historical reality, not least because it allows us retain an important manuscript reading and construe the passage as relying on an inductive generalization rather than a possibly circular argument. Ultimately, Plato fails to fully capitalize on the resources he has for a more egalitarian conclusion than the one he settles on, which regards women as “lesser than” yet “similar to” men.

Verba Transitif dan Objek Dapat Lesap dalam Bahasa Karo (Transitive Verb and Deletable Object in Karo Language)

Penelitian ini berfokus kepada objek dapat lesap di dalam verba transitif bahasa Karo yang dianalisis dengan cara menganalisis kalimat atau klausa yang ber-objek dapat lesap yang terjadi dikarenakan objek sudah di tulis dalam konteks sebelumnya, dan verba transitif yang menyatakan perasaan yang berafiks me-ken dengan berbentuk dasar adjektiva/ keadaan, verba subtipe pertama memiliki ciri dapat disertai O dan dapat dipasifkan. Pengumpulan data melalui metode tahap pengumpulan data, analisis data, dan generalisasi secara induktif. Data yang didapat dianalisis menggunakan teknik lesap menurut Sudaryanto. Temuan menunjukkan verba transitif dalam bahasa karo berafiks er-, me-, er-ken, me-kan, memper-I, dan fungsi O dituntut hadir dalam klausa yang fungsi P-nya di isi oleh verba polimorfemik dan di bahasa Karo tidak semua verba berprefiks adanya suatu peluluhan, ataupun pelesapan morfemis.Kata kunci: verba transitif, objek dapat lesap, bahasa KaroABSTRACTThis research focuses on objects that can be absorbed in the transitive verbs of Karo language analyzed by analyzing sentences or clauses that have objects that can occur due to objects that have been written in the previous context, and transitive verbs that express feelings that are me-ken with form base of adjectives / states, the first subtype verb has a characteristic can be accompanied by O and can be passivated. Data collection through the method of data collection, data analysis, and inductive generalization. The data obtained were analyzed using removal techniques according to Sudaryanto. The findings show that the transitive verbs in karo language have er-, m, er-ken, me-me, make-I, and O functions are required to be present in clauses whose P functions are filled with polymorphic verbs and not all verbs in Karo reflex the presence of an elimination, or the morphemic removal.

Automated formal synthesis of provably safe digital controllers for continuous plants

We present a sound and automated approach to synthesizing safe, digital controllers for physical plants represented as time-invariant models. Models are linear differential equations with inputs, evolving over a continuous state space. The synthesis precisely accounts for the effects of finite-precision arithmetic introduced by the controller. The approach uses counterexample-guided inductive synthesis: an inductive generalization phase produces a controller that is known to stabilize the model but that may not be safe for all initial conditions of the model. Safety is then verified via bounded model checking: if the verification step fails, a counterexample is provided to the inductive generalization, and the process further iterates until a safe controller is obtained. We demonstrate the practical value of this approach by automatically synthesizing safe controllers for physical plant models from the digital control literature.

Sampling assumptions in inductive generalization

Inductive generalization, where people go beyond the data provided, is a basic cognitive capability, and it underpins theoretical accounts of learning, categorization, and decision making. To complete the inductive leap needed for generalization, people must make a key ‘‘sampling’’ assumption about how the available data were generated. Previous models have considered two extreme possibilities, known as strong and weak sampling. In strong sampling, data are assumed to have been deliberately generated as positive examples of a concept, whereas in weak sampling, data are assumed to have been generated without any restrictions. We develop a more general account of sampling that allows for an intermediate mixture of these two extremes, and we test its usefulness. In two experiments, we show that most people complete simple one‐dimensional generalization tasks in a way that is consistent with their believing in some mixture of strong and weak sampling, but that there are large individual differences in the relative emphasis different people give to each type of sampling. We also show experimentally that the relative emphasis of the mixture is influenced by the structure of the available information. We discuss the psychological meaning of mixing strong and weak sampling, and possible extensions of our modeling approach to richer problems of inductive generalization.

Similarity, feature discovery, and the size principle

In this paper we consider the “size principle” for featural similarity, which states that rare features should be weighted more heavily than common features in people’s evaluations of the similarity between two entities. Specifically, it predicts that if a feature is possessed by n objects, the expected weight scales according to a 1/n law. One justification of the size principle emerges from a Bayesian analysis of simple induction problems (Tenenbaum and Griffiths, 2001a, Tenenbaum and Griffiths, 2001b), and is closely related to work by Shepard (1987) proposing universal laws for inductive generalization. In this article, we (1) show that the size principle can be more generally derived as an expression of a form of representational optimality, and (2) present analyses suggesting that across 11 different data sets in the domains of animals and artifacts, human judgments are in agreement with this law. A number of implications are discussed.

Middle school students' and mathematicians' judgments of mathematical typicality

K-12 students often rely on testing examples to explore and determine the truth of mathematical conjectures. However, little is known about how K-12 students choose examples and what elements are important when considering example choice. In other domains, experts give explicit consideration to the typicality of examples – how representative a given item is of a general class. In a pilot study, we interviewed 20 middle school students who classified examples as typical or unusual and justified their classification. We then gave middle school students and mathematicians a survey where they rated the typicality of mathematical objects in two contexts – an everyday context (commonness in everyday life) and a mathematical context (how likely conjectures that hold for the object are to hold for other objects). Mathematicians had distinct notions of everyday and mathematical typicality – they recognized that the objects often seen in everyday life can have mathematical properties that can limit inductive generalization. Middle school students largely did not differentiate between everyday and mathematical typicality – they did not view special mathematical properties as limiting generalization, and rated items similarly regardless of context. These results suggest directions for learning mathematical argumentation and represent an important step towards understanding the nature of typicality in math.

The Distinction between Psychological Kinds and Natural Kinds Revisited: Can Updated Natural-Kind Theory Help Clinical Psychological Science and beyond Meet Psychology's Philosophical Challenges?

Philosophers and psychologists have long held that mind-dependent/human (or social) kinds are not natural kinds. Yet in the last three decades philosopher of science Richard Boyd has challenged this belief to widespread acclaim in the philosophy of biology, where the natural-kind status of species taxa has been debated. Boyd proposed that natural-kind status hinges not on a kind's mind independence or on demonstration of its essential properties but rather on whether it supports inductive generalization, in which case it is a “homeostatic property cluster” (HPC) kind. Boyd indicates that any human/mental kind can in principle be a natural kind, without physical reduction of its properties, as long as it constitutes an HPC kind and so can be studied by way of the causal mechanisms that, he theorizes, underlie all natural kinds. In the last decade Boyd's HPC theory of natural kinds has influenced theory of mental disorder kinds and shares commonality with Denny Borsboom's burgeoning “symptom network” approach to psychiatric diagnosis. It therefore warrants more thoroughgoing theoretical and empirical analysis. This article revisits the heterogeneity that inheres in DSM categories and motivated alternative approaches, such as the Research Domain Criteria (RDoC) of the NIMH. Also assessed are two worries about the future of “HPC kinds” of mental disorder kinds: (a) ontological relativism and reification, and (b) epistemic perspectivalism and relativistic knowledge. Though focused on clinical kinds, this analysis has implications for psychological science beyond its clinical subdiscipline.