Education is a developmental process that may be improved by using a range of strategies to develop engaging classes. It stands for the educators' personal philosophy and utmost aspiration. This study aimed to assess and identify the strategies, methods, and trends of teaching-learning on students’ perspectives and their effectiveness in the new normal of education. The study employed the descriptive approach with a quantitative research design in analyzing the strategies, methods, and trends of teaching-learning. The participants of the study are (...) the professional teachers in the selected 2 public schools in the Agusan del Sur division under the San Luis District, particularly at San Luis National High School and San Mariano Elementary School. Based on the findings, it was gleaned from the findings, it was definitely concluded that the overall weighted mean value was 4.08 with a descriptive level of observation and interpretation of very satisfied based on the results. Additionally, it was revealed that the z-computed value in the result obtained with 105.329 is greater than the z-critical value of 1.87, which definitely resulted in the rejection of the hypothesis of the study. Thus, there is a statistically significant difference in the strategies, methods, and trends of teaching in the new normal learning perspective as observed by the participants of the study. Therefore, the strategies, methods, and trends in teaching shows to lay the foundation of why and how to conduct the class and helps set expectations by the students at school, also creating a shared class culture where students take more responsibility and understanding for their class participation. (shrink)

Education is a developmental process that may be improved by using a range of strategies to develop engaging classes. It stands for the educators' personal philosophy and utmost aspiration. This study aimed to assess and identify the strategies, methods, and trends of teaching-learning on students’ perspectives and their effectiveness in the new normal of education. The study employed the descriptive approach with a quantitative research design in analyzing the strategies, methods, and trends of teaching-learning. The participants of the study are (...) the professional teachers in the selected 2 public schools in the Agusan del Sur division under the San Luis District, particularly at San Luis National High School and San Mariano Elementary School. Based on the findings, it was gleaned from the findings, it was definitely concluded that the overall weighted mean value was 4.08 with a descriptive level of observation and interpretation of very satisfied based on the results. Additionally, it was revealed that the z-computed value in the result obtained with 105.329 is greater than the z-critical value of 1.87, which definitely resulted in the rejection of the hypothesis of the study. Thus, there is a statistically significant difference in the strategies, methods, and trends of teaching in the new normal learning perspective as observed by the participants of the study. Therefore, the strategies, methods, and trends in teaching shows to lay the foundation of why and how to conduct the class and helps set expectations by the students at school, also creating a shared class culture where students take more responsibility and understanding for their class participation. (shrink)

Teachers began preparing for modular and interactive distance learning under the presumption that teaching would continue regardless of the situation. Teaching is attainable, but there are difficulties as well. This quantitative study was to investigate and describe how teachers coped during the COVID-19 pandemic, including innovative practices used by teachers to defeat or simply overcome the difficulties and challenges of the modular teaching and learning approach. The study employed a descriptive-correlational research design and utilizing a purposive random sampling technique in (...) selecting the respondents of the study. There was a total of 50 public school teachers across the study’s locale who responded to the conduct survey, which set the research sample size limitation. The findings of the study showed that the significant relationship between theinnovative practices and coping mechanisms of the educators and their ability to overcome the difficulties and challenges of the modular instruction and learning approach during the COVID-19 pandemic had the overall correlation coefficient of 0.642 with a sig. (2-tailed of 0.397). Teachers must fortify their hearts to carry out their work and responsibilities despite the greater circumstances. To succeed and develop into a frontline teacher who is effective, they must devote all their effort. (shrink)

Abstract: Artificial Intelligence (AI) has rapidly evolved, offering transformative capabilities for business decision-making. This paper explores how AI can be leveraged to enhance strategic decision-making in business contexts. It examines the integration of AI-driven analytics, predictive modeling, and automation to improve decision accuracy and operational efficiency. By analyzing current applications and case studies, the paper highlights the opportunities AI presents, including enhanced data insights, risk management, and personalized customer experiences. Additionally, it addresses the challenges businesses face in adopting AI, such (...) as data privacy concerns, integration issues, and the need for skilled personnel. The paper concludes with recommendations for effectively implementing AI solutions to maximize their benefits while navigating potential pitfalls. (shrink)

The proposed model in this paper employs different integrated detectors, such as heat, smoke, and flame. The signals from those detectors go through the system algorithm to check the fire's potentiality and then broadcast the predicted result to various parties using GSM modem associated with the GSM network system. The system uses various sensors to detect fire, smoke, and gas, then transmits the message using GSM module. After the message, send by the module the help arrives in 15 minutes. The (...) system is associated with water pump and a sprinkler. The Water system is associated with a water tank and a sprinkler. The water tank uses a Ultrasonic sensor to monitor the level of water level in the tank for refilling the water tank. Once fire is detected, it automatically sends the emergency message and sprinkles the water. (shrink)

The World Health Organization has declared the outbreak of the novel coronavirus, Covid-19 as pandemic across the world. With its alarming surge of affected cases throughout the world, lockdown, and awareness (social distancing, use of masks etc.) among people are found to be the only means for restricting the community transmission. In a densely populated country like India, it is very difficult to prevent the community transmission even during lockdown without social awareness and precautionary measures taken by the people. Recently, (...) several containment zones had been identified throughout the country and divided into red, orange and green zones, respectively. The red zones indicate the infection hotspots, orange zones denote some infection and green zones indicate an area with no infection. Contact tracing is known to be an effective technique for detecting and monitoring persons who may have been exposed to individuals infected with any communicable disease. While a good number of contact tracing schemas are existent today (eg., in-person and phone interviews, paper forms, email and web based questionnaires and smartphone apps), they often require active user participation and might miss certain COVID-19 transmission. The Android application updates the locations of the areas in a Google map which are identified to be the containment zones. The application also notifies the users if they have entered a containment zone and to achieve all these functionalities, many tools, and APIs from Google like Firebase and Geofencing API are used in this application. Therefore, this application can be used as a tool for creating further social awareness about the arising need of precautionary measures to be taken by the people of India. (shrink)

It is tempting to think that a process of choosing a point at random from the surface of a sphere can be probabilistically symmetric, in the sense that any two regions of the sphere which differ by a rotation are equally likely to include the chosen point. Isaacs, Hájek, and Hawthorne (2022) argue from such symmetry principles and the mathematical paradoxes of measure to the existence of imprecise chances and the rationality of imprecise credences. Williamson (2007) has argued from a (...) related symmetry principle to the failure of probabilistic regularity. We contend that these arguments fail, because they rely on auxiliary assumptions about probability which are inconsistent with symmetry to begin with. We argue, moreover, that symmetry should be rejected in light of this inconsistency, and because it has implausible decision- theoretic implications. -/- The weaker principle of probabilistic invariance says that the probabilistic comparison of any two regions is unchanged by rotations of the sphere. This principle supports a more compelling argument for imprecise probability. We show, however, that invariance is incompatible with mundane judgments about what is probable. Ultimately, we find reason to be suspicious of the application of principles like symmetry and invariance to nonmeasurable regions. (shrink)

Cardiovascular diseases (CVD) represent a significant cause of morbidity and mortality worldwide, necessitating early detection for effective intervention. This research explores the application of machine learning (ML) algorithms in predicting cardiovascular diseases with enhanced accuracy by integrating optimization techniques. By leveraging data-driven approaches, ML models can analyze vast datasets, identifying patterns and risk factors that traditional methods might overlook. This study focuses on implementing various ML algorithms, such as Decision Trees, Random Forest, Support Vector Machines, and Neural Networks, optimized through (...) techniques like hyperparameter tuning, cross-validation, and feature selection to improve prediction accuracy. (shrink)

As inductive decision-making procedures, the inferences made by machine learning programs are subject to underdetermination by evidence and bear inductive risk. One strategy for overcoming these challenges is guided by a presumption in philosophy of science that inductive inferences can and should be value-free. Applied to machine learning programs, the strategy assumes that the influence of values is restricted to data and decision outcomes, thereby omitting internal value-laden design choice points. In this paper, I apply arguments from feminist philosophy of (...) science to machine learning programs to make the case that the resources required to respond to these inductive challenges render critical aspects of their design constitutively value-laden. I demonstrate these points specifically in the case of recidivism algorithms, arguing that contemporary debates concerning fairness in criminal justice risk-assessment programs are best understood as iterations of traditional arguments from inductive risk and demarcation, and thereby establish the value-laden nature of automated decision-making programs. Finally, in light of these points, I address opportunities for relocating the value-free ideal in machine learning and the limitations that accompany them. (shrink)

Rainfall prediction is one of the challenging tasks in weather forecasting. Accurate and timely rainfall prediction can be very helpful to take effective security measures in dvance regarding: on-going construction projects, transportation activities, agricultural tasks, flight operations and flood situation, etc. Data mining techniques can effectively predict the rainfall by extracting the hidden patterns among available features of past weather data. This research contributes by providing a critical analysis and review of latest data mining techniques, used for rainfall prediction. In (...) our proposed system we propose a new forecasting method that uses a Convolutional Neural Network monthly rainfall for a selected location. In our proposed system we are going to forecast the rainfall result based on the mean square error, mean absolute error and root mean square error, which we get in train and test of the dataset based deep learning technique. (shrink)

The problem of evil is broadly considered to be one of the greatest intellectual threats to traditional brands of theism. And William Rowe’s 1979 formulation of the problem in “The Problem of Evil and Some Varieties of Atheism” is the most cited formulation in the contemporary philosophical literature. In this paper, we explore how the tools and resources of experimental philosophy might be brought to bear on Rowe’s seminal formulation, arguing that our empirical findings raise significant questions regarding the ultimate (...) success of Rowe’s argument. Such a result would be quite notable within philosophy of religion, since this is considered one of the most formidable arguments against theism. However, further testing is needed before any firm conclusions can be drawn. -/- In section 1, we elucidate Rowe’s formulation of the problem of evil and the intuitions that seem to underwrite it. In section 2, we explore how the tools and resources of experimental philosophy might be brought to bear on Rowe’s formulation, outlining our hypotheses and our methods for testing them before showcasing our results. In section 3, we discuss the philosophical import of our results–arguing that our results, when taken together, pose an initial challenge to Rowe’s seminal argument. (shrink)

It has been a common assumption that words are substances that instantiate or have properties. In this paper, I question the assumption that our ontology of words requires posting substances by outlining a bundle theory of words, wherein words are bundles of various sorts of properties (such as semantic, phonetic, orthographic, and grammatical properties). I argue that this view can better account for certain phenomena than substance theories, is ontologically more parsimonious, and coheres with claims in linguistics.

I defend the extremist position that the fundamental ontology of the world consists of a vector in Hilbert space evolving according to the Schrödinger equation. The laws of physics are determined solely by the energy eigenspectrum of the Hamiltonian. The structure of our observed world, including space and fields living within it, should arise as a higher-level emergent description. I sketch how this might come about, although much work remains to be done.

The ever-evolving landscape of cyber threats necessitates robust and adaptable intrusion detection systems (IDS) capable of identifying both known and emerging attacks. Traditional IDS models often struggle with detecting novel threats, leading to significant security vulnerabilities. This paper proposes an optimized intrusion detection model using Support Vector Machine (SVM) algorithms tailored to detect known and innovative cyberattacks with high accuracy and efficiency. The model integrates feature selection and dimensionality reduction techniques to enhance detection performance while reducing computational overhead. By leveraging (...) advanced optimization techniques such as Grid Search and Particle Swarm Optimization (PSO), the proposed SVM-based IDS achieves superior classification results. (shrink)

Recently, bioethicists and the UNCRPD have advocated for supported medical decision-making on behalf of patients with intellectual disabilities. But what does supported decision-making really entail? One compelling framework is Anita Silvers and Leslie Francis’ mental prosthesis account, which envisions supported decision-making as a process in which trustees act as mere appendages for the patient’s will; the trustee provides the cognitive tools the patient requires to realize her conception of her own good. We argue that supported decision-making would be better understood (...) as a collaborative process, giving patients with intellectual disabilities the opportunity to make decisions in a respectful relationship with trusted others. We offer an alternative account of supported decision-making where the primary constraint is to protect the patient from domination by the trustee. This is advantageous in its preservation of the prospects for genuine collaboration, for the mental prosthesis approach ultimately reinforces a problematic ideal of isolated patient self-determination. (shrink)

The paper also discusses the technical architecture, including the network protocols, data management strategies, and user interface design considerations necessary to implement such a system. Additionally, it addresses the challenges related to data security, privacy, and system interoperability. Finally, the paper outlines potential future enhancements, such as the incorporation of AI-driven predictive analytics and advanced AR features, to further elevate the smart home experience.

The research outlines a workflow that incorporates data collection, preprocessing, model training, and optimization. Real-world datasets from retail and e-commerce sectors are utilized to validate the proposed methodology, showcasing substantial improvements in model performance. The results indicate that optimized models not only provide better predictions of consumer behaviour but also enhance customer segmentation and targeting strategies. The study concludes with recommendations for future research, including the exploration of hybrid optimization techniques and the application of these methods in real-time analytics.

Emotion detection and management have emerged as pivotal areas in humancomputer interaction, offering potential applications in healthcare, entertainment, and customer service. This study explores the use of deep learning (DL) models to enhance emotion recognition accuracy and enable effective emotion regulation mechanisms. By leveraging large datasets of facial expressions, voice tones, and physiological signals, we train deep neural networks to recognize a wide array of emotions with high precision. The proposed system integrates emotion recognition with adaptive management strategies that provide (...) personalized feedback and interventions based on detected emotional states. Our approach surpasses traditional machine learning methods, demonstrating superior performance in real-time applications. (shrink)

Many real-world agents recognise that they impose harms by choosing to emit carbon, e.g., by flying. Yet many do so anyway, and then attempt to make things right by offsetting those harms. Such offsetters typically believe that, by offsetting, they change the deontic status of their behaviour, making an otherwise impermissible action permissible. Do they succeed in practice? Some philosophers have argued that they do, since their offsets appear to reverse the adverse effects of their emissions. But we show that (...) they do not. In practice, standard carbon offsetting does not reverse the harms of the original action, nor does it even benefit the same group as was harmed. Standard moral theories hence deny that such offsetting succeeds. Indeed, we show that any moral theory that allows offsetting in this setting faces a dilemma between allowing any wrong to be offset, no matter how grievous, and recognising an implausibly sharp discontinuity between offsettable actions and non-offsettable actions. The most plausible response is to accept that carbon offsetting fails to right our climate wrongs. (shrink)

We have a much better understanding of physics than we do of consciousness. I consider ways in which intrinsically mental aspects of fundamental ontology might induce modifications of the known laws of physics, or whether they could be relevant to accounting for consciousness if no such modifications exist. I suggest that our current knowledge of physics should make us skeptical of hypothetical modifications of the known rules, and that without such modifications it’s hard to imagine how intrinsically mental aspects could (...) play a useful explanatory role. Draft version of a paper submitted to Journal of Consciousness Studies, special issue responding to Philip Goff’s Galileo’s Error: Foundations for a New Science of Consciousness. (shrink)

Some modern cosmological models predict the appearance of Boltzmann Brains: observers who randomly fluctuate out of a thermal bath rather than naturally evolving from a low-entropy Big Bang. A theory in which most observers are of the Boltzmann Brain type is generally thought to be unacceptable, although opinions differ. I argue that such theories are indeed unacceptable: the real problem is with fluctuations into observers who are locally identical to ordinary observers, and their existence cannot be swept under the rug (...) by a choice of probability distributions over observers. The issue is not that the existence of such observers is ruled out by data, but that the theories that predict them are cognitively unstable: they cannot simultaneously be true and justifiably believed. (shrink)

In today's data-driven world, the efficient management of network resources is crucial for optimizing performance in data centers and large-scale networks. Load balancing is a critical process in ensuring the equitable distribution of data across multiple paths, thereby enhancing network throughput and minimizing latency. This paper presents a comprehensive approach to load balancing using advanced optimization techniques integrated with multipath routing protocols. The primary focus is on dynamically allocating network resources to manage the massive volume of data generated by modern (...) applications. By leveraging algorithms such as Genetic Algorithms (GA) and Particle Swarm Optimization (PSO), the proposed method efficiently distributes data across multiple paths, ensuring balanced network utilization. The combination of these algorithms with multipath routing significantly reduces congestion and improves overall network performance. (shrink)

The genetic modification of pigs as a source of transplantable organs is one of several possible solutions to the chronic organ shortage. This paper describes existing ethical tensions in xenotransplantation (XTx) that argue against pursuing it. Recommendations for lifelong infectious disease surveillance and notification of close contacts of recipients are in tension with the rights of human research subjects. Parental/guardian consent for pediatric xenograft recipients is in tension with a child’s right to an open future. Individual consent to transplant is (...) in tension with public health threats that include zoonotic diseases. XTx amplifies concerns about justice in organ transplantation and could exacerbate existing inequities. The prevention of infectious disease in source animals is in tension with the best practices of animal care and animal welfare, requiring isolation, ethologically inappropriate housing, and invasive reproductive procedures that would severely impact the well-being of intelligent social creatures like pigs. (shrink)

Waiting time is widely used in health and social policy to make resource allocation decisions, yet no general account of the moral significance of waiting time exists. We provide such an account. We argue that waiting time is not intrinsically morally significant, and that the first person in a queue for a resource does not ipso facto have a right to receive that resource first. However, waiting time can and sometimes should play a role in justifying allocation decisions. First, there (...) is a duty of fairness prohibiting line-cutting where a sufficiently just queue exists. Second, waiting time has several morally attractive features that can justify its incorporation into allocation schemes. Where candidates are in relevantly similar circumstances, allocating by waiting time is relatively efficient, maximizes distribution equality relative to other Pareto efficient distributions, and treats candidates fairly. The claim that allocation using waiting time is fair is controversial. Some have claimed that formal lotteries are a fairer way to select among equal beneficiaries. We argue that lotteries are no fairer than allocation based on waiting time when it is equiprobable how a prospective queue will be ordered. In practice, lotteries share many of the disadvantages of queues; which is fairer will depend on contingent features of the allocation scenario. The upshot is that first-come, first-served is in fact a just way to allocate resources in many of the cases where it seems pre-theoretically compelling, and waiting time has unique normative properties which frequently justify its incorporation into resource allocation schemes. (shrink)

The concept of bias is pervasive in both popular discourse and empirical theorizing within philosophy, cognitive science, and artificial intelligence. This widespread application threatens to render the concept too heterogeneous and unwieldy for systematic investigation. This article explores recent philosophical literature attempting to identify a single theoretical category—termed ‘bias’—that could be unified across different contexts. To achieve this aim, the article provides a comprehensive review of theories of bias that are significant in the fields of philosophy of mind, cognitive science, (...) machine learning, and epistemology. It focuses on key examples such as perceptual bias, implicit bias, explicit bias, and algorithmic bias, scrutinizing their similarities and differences. Although these explorations may not conclusively establish the existence of a natural theoretical kind, pursuing the possibility offers valuable insights into how bias is conceptualized and deployed across diverse domains, thus deepening our understanding of its complexities across a wide range of cognitive and computational processes. (shrink)

Empirical philosophers of science aim to base their philosophical theories on observations of scientific practice. But since there is far too much science to observe it all, how can we form and test hypotheses about science that are sufficiently rigorous and broad in scope, while avoiding the pitfalls of bias and subjectivity in our methods? Part of the answer, we claim, lies in the computational tools of the digital humanities, which allow us to analyze large volumes of scientific literature. Here (...) we advocate for the use of these methods by addressing a number of large-scale, justificatory concerns—specifically, about the epistemic value of journal articles as evidence for what happens elsewhere in science, and about the ability of DH tools to extract this evidence. Far from ignoring the gap between scientific literature and the rest of scientific practice, effective use of DH tools requires critical reflection about these relationships. (shrink)

Cosmological models that invoke a multiverse - a collection of unobservable regions of space where conditions are very different from the region around us - are controversial, on the grounds that unobservable phenomena shouldn't play a crucial role in legitimate scientific theories. I argue that the way we evaluate multiverse models is precisely the same as the way we evaluate any other models, on the basis of abduction, Bayesian inference, and empirical success. There is no scientifically respectable way to do (...) cosmology without taking into account different possibilities for what the universe might be like outside our horizon. Multiverse theories are utterly conventionally scientific, even if evaluating them can be difficult in practice. (shrink)

In this paper, we argue that there are reasons to believe that an implicit bias for normalcy influences what are considered medically necessary treatments in psychiatry. First, we outline two prima facie reasons to suspect that this is the case. A bias for ‘the normal’ is already documented in disability studies; it is reasonable to suspect that it affects psychiatry too, since psychiatric patients, like disabled people, are often perceived as ‘weird’ by others. Secondly, psychiatry's explicitly endorsed values of well-being (...) and function are hard to measure directly, which is why we see simpler box-ticking conceptions of recovery used in large research studies. This need not be problematic, but might lead to researchers and clinicians focusing too much on treatments that promote easy-to-measure proxies for recovery, instead of what actually matters to psychiatric patients themselves. Next, we provide examples of treatments and treatment decisions within two areas – self-injury and psychosis – which are hard to explain unless we assume that an implicit and harmful normalcy bias is at work. We conclude with some suggestions for clinicians and future research. (shrink)

This paper explores the complex nature of social biases, arguing for a functional framework that recognizes their unity and diversity. The functional approach posits that all biases share a common functional role in overcoming underdetermination. This framework, I argue, provides a comprehensive understanding of how all psychological biases, including social biases, are unified. I then turn to the question of disunity, demonstrating how psychological social biases differ systematically in the mental states and processes that constitute them. These differences indicate that (...) biases at various levels of the cognitive architecture require distinct treatment along at least two dimensions: epistemic evaluation and mitigation strategies. By examining social biases through this dual lens of unity and diversity, we can more effectively identify when and how to intervene on problematic biases. Ultimately, this approach provides a nuanced understanding of the nature of social bias, offering practical guidance for addressing existing biases and proactively managing emerging biases in both human and artificial minds. (shrink)

One widely used method for allocating health care resources involves the use of cost-effectiveness analysis (CEA) to rank treatments in terms of quality-adjusted life-years (QALYs) gained. CEA has been criticized for discriminating against people with disabilities by valuing their lives less than those of non-disabled people. Avoiding discrimination seems to lead to the ’QALY trap’: we cannot value saving lives equally and still value raising quality of life. This paper reviews existing responses to the QALY trap and argues that all (...) are problematic. Instead, we argue that adopting a moderate form of prioritarianism avoids the QALY trap and disability discrimination. (shrink)

Binding specificity is a centrally important concept in molecular biology, yet it has received little philosophical attention. Here I aim to remedy this by analyzing binding specificity as a causal property. I focus on the concept’s role in drug design, where it is highly prized and hence directly studied. From a causal perspective, understanding why binding specificity is a valuable property of drugs contributes to an understanding of causal selection—of how and why scientists distinguish between causes, not just causes from (...) noncauses. In particular, the specificity of drugs is precisely what underwrites their value as experimental interventions on biological processes. (shrink)

Abstract: Ensuring the proactive detection of transaction risks is paramount for financial institutions, particularly in the context of managing credit scores. In this study, we compare different machine learning algorithms to effectively and efficiently. The algorithms used in this study were: MLogisticRegressionCV, ExtraTreeClassifier,LGBMClassifier,AdaBoostClassifier, GradientBoostingClassifier,Perceptron,RandomForestClassifier,KNeighborsClassifier,BaggingClassifier, DecisionTreeClassifier, CalibratedClassifierCV, LabelPropagation, Deep Learning. The dataset was collected from Kaggle depository. It consists of 164 rows and 8 columns. The best classifier with unbalanced dataset was the LogisticRegressionCV. The Accuracy 100.0%, precession 100.0%,Recall100.0% and the F1-score (...) 100.0%. However, the best classifier with balanced dataset was the LogisticRegressionCV. The Accuracy 100.0%, precession 100.0%, Recall 100.0% and the F1-score 100.0%. (shrink)

Knowledge representation (KR) is actually more than representation: It involves also inference, namely inference of “new” knowledge, i.e. new facts. Logic programming is a suitable KR medium, but more often than not discussions on this programming paradigm focus on aspects other than KR. In this paper, I elaborate on the general theory of logic programming and give the essentials of two of its main implementations, to wit, Prolog and Datalog, from the viewpoint of deductive computing over knowledge bases, which includes (...) deductive programming. (shrink)

Stephen Law developed a challenge to theism, known as the evil-god challenge (Law (2010) ). The evil-god challenge to theism is to explain why the theist’s responses to the problem of evil are any better than the diabolist’s – who believes in a supremely evil god – rejoinders to the problem of good, when all the theist’s ploys (theodicy, sceptical theism, etc.) can be parodied by the diabolist. In the first part of this article, I extend the evil-god challenge by (...) showing that additional theist replies to the problem of evil (more theodicies, the privation view of evil, and others) also may be appropriated, with just as much plausibility, in support of the diabolist position. In the second part of the article, I defend the evil-god challenge against several objections. (shrink)

Effective Field Theory (EFT) is the successful paradigm underlying modern theoretical physics, including the "Core Theory" of the Standard Model of particle physics plus Einstein's general relativity. I will argue that EFT grants us a unique insight: each EFT model comes with a built-in specification of its domain of applicability. Hence, once a model is tested within some domain (of energies and interaction strengths), we can be confident that it will continue to be accurate within that domain. Currently, the Core (...) Theory has been tested in regimes that include all of the energy scales relevant to the physics of everyday life (biology, chemistry, technology, etc.). Therefore, we have reason to be confident that the laws of physics underlying the phenomena of everyday life are completely known. (shrink)

We study the conservation of energy, or lack thereof, when measurements are performed in quantum mechanics. The expectation value of the Hamiltonian of a system changes when wave functions collapse in accordance with the standard textbook treatment of quantum measurement, but one might imagine that the change in energy is compensated by the measuring apparatus or environment. We show that this is not true; the change in the energy of a state after measurement can be arbitrarily large, independent of the (...) physical measurement process. In Everettian quantum theory, while the expectation value of the Hamiltonian is conserved for the wave function of the universe, it is not constant within individual worlds. It should therefore be possible to experimentally measure violations of conservation of energy, and we suggest an experimental protocol for doing so. (shrink)

We study the question of how to decompose Hilbert space into a preferred tensor-product factorization without any pre-existing structure other than a Hamiltonian operator, in particular the case of a bipartite decomposition into "system" and "environment." Such a decomposition can be defined by looking for subsystems that exhibit quasi-classical behavior. The correct decomposition is one in which pointer states of the system are relatively robust against environmental monitoring (their entanglement with the environment does not continually and dramatically increase) and remain (...) localized around approximately-classical trajectories. We present an in-principle algorithm for finding such a decomposition by minimizing a combination of entanglement growth and internal spreading of the system. Both of these properties are related to locality in different ways. This formalism could be relevant to the emergence of spacetime from quantum entanglement. (shrink)

A commonly raised criticism against celebrity culture is that it celebrates people who become famous without any connection to their skills, talents or achievements. A culture in which people become famous simply for being famous is criticized for being shallow and inauthentic. In this paper we offer a defence of celebrity by arguing against this criticism. We begin by outlining what we call the Talent Argument: celebrity is a negative cultural phenomenon because it creates and sustains fame without any connection (...) to the accomplishments that arise from an expression of talent or skill. By appealing to the metaphysics of talent and skill, we argue against the Talent Argument and propose that being a celebrity requires the skills that are necessary to acquire and maintain one’s status as a celebrity. A celebrity is more likely to be talented and successful in their expression of these skills, and even celebrities who are ‘famous for being famous’ will often display talents and skills that give rise to their fame. This means that those who critique celebrity culture should not do so by appealing to the Talent Argument. We show how our account of celebrity, talent and skill works to reject both the strong version of the Talent Argument, as well as a weaker and more plausible version of the argument we call the Valuable Talents argument. We conclude by noting that our analysis has demonstrated the need to explore more closely the kinds of skills that are necessary to cultivate celebrity status. This allows for a more nuanced understanding of what a celebrity is, and the values that are attached to celebrity culture. (shrink)

Environmental health research produces scientific knowledge about environmental hazards crucial for public health and environmental justice movements that seek to prevent or reduce exposure to these hazards. The environment in environmental health research is conceptualized as the range of possible social, biological, chemical, and/or physical hazards or risks to human health, some of which merit study due to factors such as their probability and severity, the feasibility of their remediation, and injustice in their distribution. This paper explores the ethics of (...) identifying the relevant environment for environmental health research, as judgments involved in defining an environmental hazard or risk, judgments of that hazard or risk's probability, severity, and/ or injustice, as well as the feasibility of its remediation, all ought to appeal to non-epistemic as well as epistemic values. I illustrate by discussing the case of environmental lead, a housing-related hazard that remains unjustly distributed by race and class and is particularly dangerous to children. Examining a controversy in environmental health research ethics where researchers tested multiple levels of lead abatement in lead-contaminated households, I argue that the broader perspective on the ethics of environmental health research provided in the first part of this paper may have helped prevent this controversy. (shrink)

Psychiatric patients sometimes ask where to draw the line between who they are – their selves – and their mental illness. This problem is referred to as the self-illness ambiguity in the literature; it has been argued that solving said ambiguity is a crucial part of psychiatric treatment. I distinguish a Realist Solution from a Constructivist one. The former requires finding a supposedly pre-existing border, in the psychiatric patient’s mental life, between that which belongs to the self and that which (...) belongs to the mental illness. I argue that no such border exists, and that attempts to find it might even render the felt ambiguity worse. Instead, any solution must be constructivist; the patient (and others) should deliberate and discuss what to identify with or not. I further argue that psychiatric patients need not see their mental illness as wholly distinct from themselves to avoid ‘identifying with their diagnoses' in a problematic way. Finally, we can excuse problematic behaviour by mentally ill people – in fact, we can do so in a more nuanced and constructive way – while rejecting the view that the mental illness is wholly distinct from the patient’s self. (shrink)

We critique two popular philosophical definitions of intellectual humility: the “low concern for status” and the “limitations-owning.” accounts. Based upon our analysis, we offer an alternative working definition of intellectual humility: the virtue of accurately tracking what one could non-culpably take to be the positive epistemic status of one’s own beliefs. We regard this view of intellectual humility both as a virtuous mean between intellectual arrogance and diffidence and as having advantages over other recent conceptions of intellectual humility. After defending (...) this view, we sketch remaining questions and issues that may bear upon the psychological treatment of intellectual humility such as whether evidence will help determine how this construct relates to general social humility on the one hand, and intellectual traits such as open-mindedness, curiosity, and honesty on the other. (shrink)

In this paper I investigate central temporal and spatial notions in the second part of Plato’s Parmenides and argue that also these notions, and not only the metaphysical ones usually discussed in the literature, can be understood as a response to positions and problems put on the table by Parmenides and Zeno. Of the spatial notions examined in the dialogue, I look at the problems raised for possessing location and shape, while with respect to temporal notions, I focus on the (...) discussion of ‘being in time’ and exaiphnês (the latter notion will be shown to be also an important influence for Aristotle’s Physics). In displaying a paradoxical character and taking up crucial notions from Parmenides, the second part of the Parmenides seems to display some resemblance to Zeno’s paradoxes. I will show, however, that in contrast to Zeno, the second part of Plato’s Parmenides also demonstrates Parmenides’ One to be problematic on its own terms. Furthermore, the dialogue presents not only important problems that these spatial and temporal notions seem to lead us into, but also establishes some positive features necessary to think of time and space. In this way, Plato’s Parmenides can be seen as contributing to the development of temporal and spatial conceptualisations in ancient Greek thought. (shrink)

It seems natural to ask why the universe exists at all. Modern physics suggests that the universe can exist all by itself as a self-contained system, without anything external to create or sustain it. But there might not be an absolute answer to why it exists. I argue that any attempt to account for the existence of something rather than nothing must ultimately bottom out in a set of brute facts; the universe simply is, without ultimate cause or explanation.

[COMMENTARY on Walter Veit's "A Philosophy for the Science of Animal Consciousness"] The framework Veit introduces for animal consciousness turns on finding and articulating its evolutionary origins. Veit argues that consciousness first evolved as affective experience in the Cambrian period. His argument centers around the plausible need of organisms in the Cambrian for a common currency of subjective valuation. I argue that such an adaptive pressure is unlikely to result in affective experience. I review other processes that instantiate common currencies (...) of subjective valuation: unconscious (non-experiential) affect and the reward learning system and argue that each is likely to have evolved prior to affective experience. (shrink)

The natural name theory, recently discussed by Johnson (2018), is proposed as an explanation of pure quotation where the quoted term(s) refers to a linguistic object such as in the sentence ‘In the above, ‘bank’ is ambiguous’. After outlining the theory, I raise a problem for the natural name theory. I argue that positing a resemblance relation between the name and the linguistic object it names does not allow us to rule out cases where the natural name fails to resemble (...) the linguistic object it names. I argue that to avoid this problem, we can combine the natural name theory with a type-realist metaphysics of language, and hold that the name is natural because the name is an instance of the kind that it names. I conclude by reflecting on the importance of the metaphysics of language for questions in the philosophy of language. (shrink)

In recent analytic literature on the Trinity we have seen a variety of "social" models of the Trinity. By contrast there are few "non-­‐social" models. One prominent "non-­‐social" view is Brian Leftow's "Latin Trinity." I argue that the name of Leftow's model is not sufficiently descriptive in light of diverse models within Latin speaking theology. Next, I develop a new "non-­‐social" model that is inspired by Richard of St. Victor's description of a person in conjunction with my appropriating insights about (...) indexicals from David Kaplan and John Perry. I point out that the copula in tokens of statements like, "I am the Father," is an ambiguous term and when used by a certain divine person a different proposition is affirmed. Central to this model is the claim that the copula bears the "is of identity" and the "is of numerical sameness without identity." Further, I show that Leftow's model employs two concepts of "person," a Lockean one and a Boethian one, and mine employs Richard of St. Victor's. I describe Leftow's model as a "hard non-­‐social" model and mine as a "soft non-­‐social" model that is nearer to some social models. I conclude that Leftow's model is not the lone candidate among "non-­‐social" models and that the variety of "non-­‐social" models has yet to be exhausted. (shrink)

Jacques Monod (1971) argued that certain molecular processes rely critically on the property of chemical arbitrariness, which he claimed allows those processes to “transcend the laws of chemistry”. It seems natural, as some philosophers have done, to interpret this in modal terms: a biological relationship is chemically arbitrary if it is possible, within the constraints of chemical “law”, for that relationship to have been otherwise than it is. But while modality is certainly important for understanding chemical arbitrariness, understanding its biological (...) role also requires an account of the concrete causal-functional features that distinguish arbitrary from non-arbitrary phenomena. In this paper I elaborate on this under-emphasised aspect by offering a general account of these features: arbitrary relations are instantiated by mechanisms that involve molecular adapters, which causally couple two properties or processes which would otherwise be uncorrelated. Additionally, adapters work by acting as intermediate rather than cooperating causes. (shrink)

We often appeal to the notion of an agent’s commitment to action to characterize, e.g., an agent’s faithfulness to a promise she has given to another, her robust disposition to pursue a goal she values or cares about, and her determination to stick to that goal. In the philosophy of action, that notion is often associated with the idea of an agent’s intention to act. In ethics, it is associated primarily with the idea of an agent’s commitment to, or endorsement (...) of, a certain norm. This essay argues that both these ideas, of intention and of normative endorsement, are central to the –or, at least, an—ordinary notion of an agent’s (psychological) commitment to action. In so doing, the essay also sheds light on important features of intention. -/- Keywords: commitment – intention – normative endorsement – stability across contexts – coordination. (shrink)

It is traditional to ascribe to Locke the view that every person who acquires natural property rights by labouring on resources is obligated to leave sufficient resources for everyone else. But during the last several decades, a number of authors have contributed to a compelling textual case against this reading. Nevertheless, Locke clearly indicates that there is something wrong with distributions in which some suffer while others thrive. But if he does not endorse the traditional proviso, what exactly is the (...) problem? In this paper, I offer a solution to this puzzle. I argue that according to Locke, once people use their natural rights to acquire large properties, many individuals are unable to enjoy the material and moral wellbeing, or “preservation,” that is the end of natural law. For even if such large properties pose no problem for material preservation, they foster arbitrary power that offends against moral preservation. (shrink)

The introduction to a special issue of Religious Studies on the theme of experimental philosophy of religion.