As a retired professor, I join in the growing concerns among educators, and others, about plagiarism, especially now that AI tools like ChatGPT are so readily available. However, I feel more caution is needed, regarding temptations to rely on supposed automatic detection tools, like Turnitin, to solve the problems. Students can be unfairly accused if such tools are used unreflectingly. The Toronto Star's online version of this published Op Ed is available at the link shown below. The version attached here (...) is a pre-print, which also includes annotations for my references, which are not displayed in the published version. (shrink)

DOI: 10.1080/00031305.2018.1564697 When the editors of Basic and Applied Social Psychology effectively banned the use of null hypothesis significance testing (NHST) from articles published in their journal, it set off a fire-storm of discussions both supporting the decision and defending the utility of NHST in scientific research. At the heart of NHST is the p-value which is the probability of obtaining an effect equal to or more extreme than the one observed in the sample data, given the null hypothesis and (...) other model assumptions. Although this is conceptually different from the probability of the null hypothesis being true, given the sample, p-values nonetheless can provide evidential information, toward making an inference about a parameter. Applying a 10,000-case simulation described in this article, the authors found that p-values’ inferential signals to either reject or not reject a null hypothesis about the mean (α = 0.05) were consistent for almost 70% of the cases with the parameter’s true location for the sampled-from population. Success increases if a hybrid decision criterion, minimum effect size plus p-value (MESP), is used. Here, rejecting the null also requires the difference of the observed statistic from the exact null to be meaningfully large or practically significant, in the researcher’s judgment and experience. The simulation compares performances of several methods: from p-value and/or effect size-based, to confidence-interval based, under various conditions of true location of the mean, test power, and comparative sizes of the meaningful distance and population variability. For any inference procedure that outputs a binary indicator, like flagging whether a p-value is significant, the output of one single experiment is not sufficient evidence for a definitive conclusion. Yet, if a tool like MESP generates a relatively reliable signal and is used knowledgeably as part of a research process, it can provide useful information. (shrink)

This paper updates (2017) a previously-presented* model of models, which can be used to clarify discussion and analysis in a variety of disputes and debates, since many such discussions hinge on displaying or implying models about how things are related. Knowing about models does not itself supply any new information about our world, but it might help us to recognize when and how information is being conveyed on these matters, or where possibly it is being obscured. If a claim P (...) is expressed in the context of a certain model, a disagreement about P may actually not be about whether the underlying model is accurate; it could reflect misunderstandings about the model’s assumptions or conventions. Also, in practice, constructed models are rarely fully elaborated for every detail, so misunderstandings can arise from apparent “gaps” in the model. In that case, developing and considering complementary versions of models can sometimes clarify ambiguities. Following the main analysis are several extended Case examples to illustrate the wide applicability of the models approach, for clarifying, if not necessarily “resolving”, numerous debates and issues. For example, a famous “counter example” by Nelson Goodman to a logical model proposed by Carnap is shown to be not as deal-breaking as presumed historically, if only plausible complementary models had been explored. And models sometimes presented as competing in Artificial Intelligence research— “Declarative” versus “Procedural”—can instead be viewed as good examples of “complementary” models. Also reconsidered in this light are some well-known, competing positions, by Russell, Strawson, and Kripke, in the literature regarding names, pointing, definite descriptions and “using” sentences, and so on. All these concepts are locatable within the presently proposed models analysis. Questions such as where “truth” resides (whether in sentences or in uses of sentences) are not settled in this paper; yet, practical questions about how testable claims about the world can be expressed by models are clarified. _* Original version presented at a University of Waterloo Philosophy Colloquium 1984. (shrink)

Although at first glance, “facts” are the paradigms of straightforwardness, something about facts seems to invite perpetual controversy and dichotomizing. Innumerable bifurcations on the topic have included "Facts vs. Theories”, “Facts vs. Appearance”, "Facts vs. Values", ... and, popular nowadays, "(Real)Facts vs. Fake Facts". This paper most aligns with the facts vs. theories model, so far as whatever facts are, theories seem to be constructed stories that are necessary for connecting and interpreting the facts. Yet the boundary between the two (...) is fluid and fuzzy: Fact in one context is theory in another, depending on what is being accepted or contested at the time. This paper’s views are compatible with—but neutral on the plausibility of having—an optimism like Peirce’s that scientific inquiry may nonetheless converge towards a consensus. To illustrate the challenges of finding “straightforward” facts, the paper includes a case example, related to research on possible health effects of exposure to electromagnetic-field radiation (EMF). _ The source paper for this 2018 update was originally presented at the University of Waterloo 30th Anniversary Philosophy Conference, 1993. (shrink)

Much research into why and how critical thinking can be taught is directed towards traditional educational contexts and students. But how can those who are already in the workforce--or who would like to be--obtain needed preparation, as adults, for gaining crucial skills in critical thinking, innovation, and problem solving? Mastery in such skills cannot be learned just by mechanical training techniques, delivered online or otherwise, and many adult-oriented materials for enhancing creativity and problem-solving seem best suited for already-prepared minds. The (...) paper invites researchers to inquire how less well-prepared adults can also succeed in bridging this gap. (shrink)

In the face of continuing assumptions by many scientists and journal editors that p-values provide a gold standard for inference, counter warnings are published periodically. But the core problem is not with p-values, per se. A finding that “p-value is less than α” could merely signal that a critical value has been exceeded. The question is why, when estimating a parameter, we provide a range (a confidence interval), but when testing a hypothesis about a parameter (e.g. µ = x) we (...) proceed as if “=” entails exact equality of the parameter with x. That standard is hard to meet, and is not a standard expected for power calculations, where we are satisfied to reject a null hypothesis H0 if the result is merely “detectably” different from (exact) H0. This paper explores, with resampling (simulation) methods, the impacts on p-values, and alternatives, if the null hypothesis is defined as a thick or thin range of values. It also examines, empirically, the extent to which the p-value may or may not be a good predictor of the probability that H0 is true, given the distribution of the data. (shrink)

This paper takes up the challenge which Carnap poses in his Aufbau: to make of it a basis for continued epistemological research. I try to close some gaps in Carnap’s original presentation and to make at least the first few steps of his constructional outline more accessible to the modern reader. Particularly emphasized is Carnap’s implicit recognition that, to be effective, “structural” models of epistemology (using logical symbols) must be complemented with “procedural” models (his “fictitious operations”). The paper shows how (...) a procedural model, a computer program,can “bypass” Nelson Goodman’s counter example to Carnap’s logical construction of “similarity circles”. (shrink)

The movement called Experimental Philosophy (‘x-Phi’) has now passed its tenth anniversary. Its central insight is compelling: When an argument hinges on accepting certain ‘facts’ about human perception, knowledge, or judging, the evoking of relevant intuitions by thought experiments is intended to make those facts seem obvious. But these intuitions may not be shared universally. Experimentalists propose testing claims that traditionally were intuition-based using real experiments, with real samples. Demanding that empirical claims be empirically supported is certainly reasonable; though experiments (...) are not necessarily the only means available. When experiments are conducted, adequately interpreting their results requires understanding the study’s design (and possibly flaws) that produced them. Experiment-based reports should document the design clearly. If Plato, writing his Meno, replaced accounts of Socrates demonstrating geometry to a slave-boy, with a survey of 100 real boys—some grasping his demonstrations, others not—what conclusions could be reached? Before answering, the reader needs details on key design questions, including (among others): (a) What population are these samples intended to represent? (E.g., ‘all slave boys’?; ‘math-ignorant people’?; ‘everyone’?) (b) What statistical tests were conducted, on what assumptions? (c) How was ‘significance’ of results determined? (d) Was the test instrument’s validity established? For readers wishing to explore x-Phi’s potentials, as contributors or as interpreters of their findings, this paper offers some cautionary considerations. Throughout their literature, examples can be found casting doubt on some experimentalists’ findings, due to design-related issues. Increased awareness of methodological questions would tighten the x-phi literature, going forward . (shrink)

A model is proposed for interpreting the course of Western Science’s conception of mathematics from the time of the ancient Greeks to the present day. According to this model, philosophy of science, in general, has traced a horseshoe-shaped curve through time. The ‘horseshoe’ emerges with Pythagoras and other Greek scientists and has curved ‘back’—but not quite back—towards modern trends in philosophy of science, as for example espoused by Bas van Fraassen. Two features of a horseshoe are pertinent to this metaphor: (...) (1) The horseshoe’s semicircular shape models the emergence of science from monism towards dualism, and its modern return towards unity. (2) The logical ‘horseshoe’ operator (“if…then”) makes possible the logical rule ‘modus ponens’--so central to Western science’s deductive approach (which is reaching its limits). Descartes fits approximately at the turning point of the curve. ‘Where might the curve go next?’ is posed to the reader. (shrink)

After some years (or millennia) most works would no longer be considered eligible for "review." But an exception is called for, if the thrust of an older work is closely paralleled in a much more modern piece, as is the case between Plato's Theaetetus and Richard Rorty's acclaimed, and more recent volume, Philosophy and the Mirror of Nature. To fully understand and appreciate Rorty 's contribution to the subjects he raises, one must study his book in conjunction with Plato's Theaetetus-where (...) very similar issues have been discussed before. Both works concern a central question for philosophy: "What is knowledge?" The discussants in Plato's dialogue the Theaetetus, never do succeed in finding a satisfactory definition for knowledge, yet they at least realize to avoid thinking they know about the subject when, in fact, they lack that knowledge. Since Rorty explores some new (and not so new) ideas on these topics, Plato's discussants ask him a few questions. (Reprinted from original in Antioch Review). (shrink)

In response to rapid technological changes in our society, there are calls by governments and industry for increased training of the workforce. But training alone is not sufficient to ensure success, even if talent, discipline and good fortune are all amply provided. When “training” goals require creativity, or decision making, or moral judgment, then adequate preparation must also include “education” in John Dewey’s sense—that is, imparting abilities to solve new problems and grasp novel meanings. Concluding this small monograph is a (...) proposed research agenda, which includes exploring the crucial role of “intuition” and related processes in abilities to generate hypotheses and solve problems. In its elaboration on the nature and limits of training, compared to education, the discussion includes a Thought Experiment, based on Bernard Suits’ exploration of rules and success in playing games. (shrink)

This mini-monograph supplements the author’s “Beyond Competence,” which is also posted on this site. The latter asks how training is accomplished. But training success is ultimately judged by one’s success at the trained-for tasks. This leads to asking: “What makes people succeed at their tasks?” If this could be known, then preparation could be more effective. Such influences as training, talent, chance, and discipline are considered. Yet, for goals requiring creativity, decision making, or moral judgment, we find that training alone (...) cannot ensure success. In its elaboration on the issues for success, the discussion expands on the Thought Experiment, begun in “Beyond Competence,” based on Bernard Suits’ analyses of playing games. (shrink)

This paper takes up the challenge which Carnap poses in his Aufbau: to make of it a basis for continued epistemological research. I try to close some gaps in Carnap’s original presentation and to make at least the first few steps of his constructional outline more accessible to the modern reader. Particularly emphasized is Carnap’s implicit recognition that, to be effective, “structural” models of epistemology (using logical symbols) must be complemented with “procedural” models (his “fictitious operations”). The paper shows how (...) a procedural model, a computer program,can “bypass” Nelson Goodman’s counter example to Carnap’s logical construction of “similarity circles”. (shrink)

Goodman draws together, in this memoir, his explorations of meaning and coincidence, and his lived experiences of chance, and his professional experiences teaching, writing, and consulting about risk. The book opens by describing the author's life-changing encounter with a Zen Buddhist monk in 1977, over a cup of tea. Returning to his beginnings, Goodman recounts his coming-of-age, from participating the 1960’s U.S. protests and Vietnam-War resistance, to finally settling down in Canada. He describes his role in a supporting, silent vigil (...) around Willard Straight Hall at Cornell University, the night after it had been occupied by protestors, and his later application for Conscientious Objector status, following the U.S. draft lottery in 1969. He reflects on the challenges and changes on his road taken, in his career and personal relationships, and in spiritual searches, to share some insights about the seamless nature of chance, and about seeing a Both/And perspective in life that encourages openness to possibilities. -/- . (shrink)