Every rational person knows that there is a finite limit to the carrying capacity of the earth. No ecologist was needed to tell us this, for the statement that finite systems cannot sustain infinite magnitudes is a truth of logic no sane person can choose to ignore and still claim to be rational. The question concerning how we shall approach the limits to population growth, and at what cost, is still an open question. Human beings have increasingly taken on (...) a "cybernetic role" in the ecosystem which sustains them. The question facing humankind relative to population control is, Will the cybernetic role of human beings on the earth's ecosystem be expanded to include the regulation of human numbers, or will nature reassume this function? If this role in regulating human numbers is assumed by people, what forms will it take? (shrink)

It is often claimed that reducing population size would be advantageous for climate change mitigation, on the grounds that lower population would naturally correspond to lower emissions. This apparently obvious claim is in fact seriously misleading. Reducing population size would indeed, other suitable things being equal, reduce the emissions rate. But it is well recognised that the primary determinant of the eventual amount of climate change is not the emissions rate, but rather cumulative emissions. It is far (...) less clear whether reducing population size would reduce cumulative emissions, or would in any other way prove an advantage for reasons related to climate change. This paper identifies and briefly discusses the issues relevant to assessing that less clear question. (shrink)

This essay introduces a new type of measure of social welfare, where populations are evaluated by their resemblance to an optimum population, which is an (in principle) possible population with the highest degree of social welfare, relative to some circumstances. Here it is argued to be the largest possible population where everyone fares maximally well. The new measure is responsive to quality of welfare, equality of welfare, and the number of people. It satisfies dominance and negative (...) monotonicity, and it avoids both the repugnant conclusion and a reverse repugnant conclusion for comparisons relative to our future on earth. (shrink)

Ascertaining the optimum global population raises not just substantive moral problems but also philosophical ones, too. In particular, serious problems arise for utilitarianism. For example, should one attempt to bring about the greatest total happiness or the highest level of average happiness? This article argues that neither approach on its own provides a satisfactory answer, and nor do rights-based or Rawlsian approaches, either. Instead, what is required is a multidimensional approach to moral questions—one which recognises the plurality of (...) our values. Such an approach can be formalised by employing multidimensional indifference-curves. Moreover, whereas classical utilitarianism might be thought to enjoin us to bring about a larger global population, a multidimensional approach clearly suggests a significant reduction in human numbers. (shrink)

We describe the structure, operation, and experience of the Massachusetts General Hospital ethics committee, formally called the Edwin H. Cassem Optimum Care Committee, from January 2007 through December 2013. Founded in 1974 as one of the nation’s first hospital ethics committees, this committee has primarily focused on the optimum use of life-sustaining treatments. We outline specific sociodemographic and clinical characteristics of consult patients during this period, demographic differences between the adult inpatient population and patients for whom the (...) ethics committee was consulted, and salient features of the consults themselves. We include three case studies that illustrate important consult themes during this period. Our findings expand knowledge about the structure and workings of hospital ethics committees and illustrate how one ethics committee has developed and utilized policies on end-of-life care. More generally, we model a sociological approach to the study of clinical ethics consultation that could be utilized to contextualize institutional practices over time. (shrink)

The constraint-handling methods using multiobjective techniques in evolutionary algorithms have drawn increasing attention from researchers. This paper proposes an efficient conical area differential evolution algorithm, which employs biased decomposition and dual populations for constrained optimization by borrowing the idea of cone decomposition for multiobjective optimization. In this approach, a conical subpopulation and a feasible subpopulation are designed to search for the global feasible optimum, along the Pareto front and the feasible segment, respectively, in a cooperative way. In particular, the (...) conical subpopulation aims to efficiently construct and utilize the Pareto front through a biased cone decomposition strategy and conical area indicator. Neighbors in the conical subpopulation are fully exploited to assist each other to find the global feasible optimum. Afterwards, the feasible subpopulation is ranked and updated according to a tolerance-based rule to heighten its diversity in the early stage of evolution. Experimental results on 24 benchmark test cases reveal that CADE is capable of resolving the constrained optimization problems more efficiently as well as producing solutions that are significantly competitive with other popular approaches. (shrink)

One of the disadvantages of the point estimate in survey sampling is that it fluctuates from sample to sample due to sampling error, as the estimator only provides a point value for the parameter under discussion. The neutrosophic approach, pioneered by Florentin Smarandache, is an excellent tool for estimating the parameters under consideration in sampling theory since it yields interval estimates in which the parameter lies with a very high probability. As a result, the neutrosophic technique, which is a generalization (...) of classical approach, is used to deal with ambiguous, indeterminate, and uncertain data. In this investigation, we suggest a new general family of ratio and exponential ratio type estimators for the elevated estimation of neutrosophic population mean of the primary variable utilizing known neutrosophic auxiliary parameters. For the first degree approximation, the bias and Mean Squared Error (MSE) of the suggested estimators are computed. The neutrosophic optimum values of the characterizing constants are determined, as well as the minimum value of the neutrosophic MSE of the suggested estimator is obtained for these optimum values of the characterizing scalars. Because the minimum MSE of the classical estimators of population mean lies inside the estimated interval of the neutrosophic estimators, the neutrosophic estimators are better than the equivalent classical estimators. The empirical investigation, which used both real and simulated data sets, backs up the theoretical findings. For practical utility in various areas of applications, the estimator with the lowest MSE or highest Percentage Relative Efficiency (PRE) is recommended. (shrink)

In presence of predator population, the prey population may significantly change their behavior. Fear for predator population enhances the survival probability of prey population, and it can greatly reduce the reproduction of prey population. In this study, we propose a predator-prey fishery model introducing the cost of fear into prey reproduction with Holling type-II functional response and prey-dependent harvesting and investigate the global dynamics of the proposed model. For the system without harvest, it is shown (...) that the level of fear may alter the stability of the positive equilibrium, and an expression of fear critical level is characterized. For the harvest system, the existence of the semitrivial order-1 periodic solution and positive order- q periodic solution is discussed by the construction of a Poincaré map on the phase set, and the threshold conditions are given, which can not only transform state-dependent harvesting into a cycle one but also provide a possibility to determine the harvest frequency. In addition, to ensure a certain robustness of the adopted harvest policy, the threshold condition for the stability of the order- q periodic solution is given. Meanwhile, to achieve a good economic profit, an optimization problem is formulated and the optimum harvest level is obtained. Mathematical findings have been validated in numerical simulation by MATLAB. Different effects of different harvest levels and different fear levels have been demonstrated by depicting figures in numerical simulation using MATLAB. (shrink)

Médecins Sans Frontières (MSF) is an independent medical humanitarian organisation working in over 70 countries. It has provided medical assistance for over 35 years to populations vulnerable through conflict, disease and inadequate health systems. Medical ethics define the starting point of the relationship between medical staff and patients. The ethics of humanitarian interventions and of research in conflict settings are much debated. However, less is known about the ethical dilemmas faced by medical humanitarian staff in their daily work. Ethical dilemmas (...) can be intensified in humanitarian contexts by insecure environments, lack of optimum care, language barriers, potentially heightened power discrepancies between care providers and patients, differing cultural values and perceptions of patients, communities and medical staff. Time constraints, stressful conditions and lack of familiarity with ethical frameworks can prevent reflection on these dilemmas, as can frustration that such reflection does not necessarily provide instant solutions. Lack of reflection, however, can be distressing for medical practitioners and can reduce the quality of care. Ethical reflection has a central role in MSF, and the organisation uses ethical frameworks to help with clinical and programmatic decisions as well as in deliberations over operational research. We illustrate and discuss some real ethical dilemmas facing MSF teams. Only by sharing and seeking guidance can MSF and similar actors make more thoughtful and appropriate decisions. Our aim in sharing these cases is to invite discussion and dialogue in the wider medical community working in crisis, conflict or with severe resource limitations. (shrink)

Currently assessment and management of animal welfare are based on the supposition that welfare status is something experienced identically by each individual animal when exposed to the same conditions. However, many authors argue that individual welfare cannot be seen as an ‘objective’ state, but is based on the animal’s own self-perception; such perception might vary significantly between individuals which appear to be exposed to exactly the same challenges. We argue that this has two implications: (1) actual perceived welfare status of (...) individuals in a population may vary over a wide range even under identical environmental conditions; (2) animals that appear to an external observer to be in better or poorer welfare condition may all in fact perceive their own individual status as the same. This would imply that optimum welfare of a social group might be achieved in situations where individual group members differ markedly in apparent welfare status and perceive their own welfare as being optimal under differing circumstances. Welfare phenotypes may also vary along a continuum between self-regarding and other-regarding behaviour; a variety of situations exist where (social) individuals appear to invest in the welfare of other individuals instead of maximising their own welfare; in such a case it is necessary to re-evaluate individual welfare within the context of a social group and recognise that there may be consequences for the welfare of individuals, of decisions made at the group level or by other group members. (shrink)

ABSTRACT I argue that this examination and appreciation for the shift to abductive reasoning should be extended to the intersection of neuroscience and novel brain-computer interfaces too. This paper highlights the implications of applying abductive reasoning to personalized implantable neurotechnologies. Then, it explores whether abductive reasoning is sufficient to justify insurance coverage for devices absent widespread clinical trials, which are better applied to one-size-fits-all treatments. INTRODUCTION In contrast to the classic model of randomized-control trials, often with a large number of (...) subjects enrolled, precision medicine attempts to optimize therapeutic outcomes by focusing on the individual.[i] A recent publication highlights the strengths and weakness of both traditional evidence-based medicine and precision medicine.[ii] Plus, it outlines a tension in the shift from evidence-based medicine’s inductive reasoning style (the collection of data to postulate general theories) to precision medicine’s abductive reasoning style (the generation of an idea from the limited data available).[iii] The paper’s main example is the application of precision medicine for the treatment of cancer.[iv] I argue that this examination and appreciation for the shift to abductive reasoning should be extended to the intersection of neuroscience and novel brain-computer interfaces too. As the name suggests, brain-computer interfaces are a significant advancement in neurotechnology that directly connects someone’s brain to external or implanted devices.[v] Among the various kinds of brain-computer interfaces, adaptive deep brain stimulation devices require numerous personalized adjustments to their settings during the implantation and computation stages in order to provide adequate relief to patients with treatment-resistant disorders. What makes these devices unique is how adaptive deep brain stimulation integrates a sensory component to initiate the stimulation. While not commonly at the level of sophistication as self-supervising or generative large language models,[vi] they currently allow for a semi-autonomous form of neuromodulation. This paper highlights the implications of applying abductive reasoning to personalized implantable neurotechnologies. Then, it explores whether abductive reasoning is sufficient to justify insurance coverage for devices absent widespread clinical trials, which are better applied to one-size-fits-all treatments.[vii] ANALYSIS I. The State of Precision Medicine in Oncology and the Epistemological Shift While a thorough overview of precision medicine for the treatment of cancer is beyond the scope of this article, its practice can be roughly summarized as identifying clinically significant characteristics a patient possesses (e.g., genetic traits) to land on a specialized treatment option that, theoretically, should benefit the patient the most.[viii] However, in such a practice of stratification patients fall into smaller and smaller populations and the quality of evidence that can be applied to anyone outside these decreases in turn.[ix] As inductive logic helps to articulate, the greater the number of patients that respond to a particular therapy the higher the probability of its efficacy. By straying from this logical framework, precision medicine opens the treatment of cancer to more uncertainty about the validity of these approaches to the resulting disease subcategories.[x] Thus, while contemporary medical practices explicitly describe some treatments as “personalized”, they ought not be viewed as inherently better founded than other therapies.[xi] A relevant contemporary case of precision medicine out of Norway focuses on the care of a patient with cancer between the ventricles of the heart and esophagus, which had failed to respond to the standard regimen of therapies over four years.[xii] In a last-ditch effort, the patient elected to pay out-of-pocket for an experimental immunotherapy (nivolumab) at a private hospital. He experienced marked improvements and a reduction in the size of the tumor. Understandably, the patient tried to pursue further rounds of nivolumab at a public hospital. However, the hospital initially declined to pay for it given the “lack of evidence from randomised clinical trials for this drug relating to this [patient’s] condition.”[xiii] In rebuttal to this claim, the patient countered that he was actually similar to a subpopulation of patients who responded in “open‐label, single arm, phase 2 studies on another immune therapy drug” (pembrolizumab).[xiv] Given this interpretation of the prior studies and the patient’s response, further rounds of nivolumab were approved. Had the patient not had improvements in the tumor’s size following a round of nivolumab, then pembrolizumab’s prior empirical evidence in isolation would have been insufficient, inductively speaking, to justify his continued use of nivolumab.[xv] The case demonstrates a shift in reasoning from the traditional induction to abduction. The phenomenon of ‘cancer improvement’ is considered causally linked to nivolumab and its underlying physiological mechanisms.[xvi] However, “the weakness of abductions is that there may always be some other better, unknown explanation for an effect. The patient may for example belong to a special subgroup that spontaneously improves, or the change may be a placebo effect. This does not mean, however, that abductive inferences cannot be strong or reasonable, in the sense that they can make a conclusion probable.”[xvii] To demonstrate the limitations of relying on the abductive standard in isolation, commentators have pointed out that side effects in precision medicine are hard to rule out as being related to the initial intervention itself unless trends from a group of patients are taken into consideration.[xviii] As artificial intelligence (AI) assists the development of precision medicine for oncology, this uncertainty ought to be taken into consideration. The implementation of AI has been crucial to the development of precision medicine by providing a way to combine large patient datasets or a single patient with a large number of unique variables with machine learning to recommend matches based on statistics and probability of success upon which practitioners can base medical recommendations.[xix] The AI is usually not establishing a causal relationship[xx] – it is predicting. So, as AI bleeds into medical devices, like brain-computer interfaces, the same cautions about using abductive reasoning alone should be carried over. II. Responsive Neurostimulation, AI, and Personalized Medicine Like precision medicine in cancer treatment, computer-brain interface technology similarly focuses on the individual patient through personalized settings. In order to properly expose the intersection of AI, precision medicine, abductive reasoning, and implantable neurotechnologies, the descriptions of adaptive deep brain stimulation systems need to deepen.[xxi] As a broad summary of adaptive deep brain stimulation, to provide a patient with the therapeutic stimulation, a neural signal, typically referred to as a local field potential,[xxii] must first be detected and then interpreted by the device. The main adaptive deep brain stimulation device with premarket approval, the NeuroPace Responsive Neurostimulation system, is used to treat epilepsy by detecting and storing “programmer-defined phenomena.”[xxiii] Providers can optimize the detection settings of the device to align with the patient’s unique electrographic seizures as well as personalize the reacting stimulation’s parameters.[xxiv] The provider adjusts the technology based on trial and error. One day machine learning algorithms will be able to regularly aid this process in myriad ways, such as by identifying the specific stimulation settings a patient may respond to ahead of time based on their electrophysiological signatures.[xxv] Either way, with AI or programmers, adaptive neurostimulation technologies are individualized and therefore operate in line with precision medicine rather than standard treatments based on large clinical trials. Contemporary neurostimulation devices are not usually sophisticated enough to be prominent in AI discussions where the topics of neural networks, deep learning, generative models, and self-attention dominate the conversation. However, implantable high-density electrocorticography arrays (a much more sensitive version than adaptive deep brain stimulation systems use) have been used in combination with neural networks to help patients with neurologic deficits from a prior stroke “speak” through a virtual avatar.[xxvi] In some experimental situations, algorithms are optimizing stimulation parameters with increasing levels of independence.[xxvii] An example of neurostimulation that is analogous to the use of nivolumab in Norway surrounds a patient in the United States who was experiencing both treatment-resistant OCD and temporal lobe epilepsy.[xxviii]Given the refractory nature of her epilepsy, implantation of an adaptive deep brain stimulation system was indicated. As a form of experimental therapy, her treatment-resistant OCD was also indicated for the off-label use of an adaptive deep brain stimulation set-up. Another deep brain stimulation lead, other than the one implanted for epilepsy, was placed in the patient’s right nucleus accumbens and ventral pallidum region given the correlation these nuclei had with OCD symptoms in prior research. Following this, the patient underwent “1) ambulatory, patient-initiated magnet-swipe storage of data during moments of obsessive thoughts; (2) lab-based, naturalistic provocation of OCD-related distress (naturalistic provocation task); and (3) lab-based, VR [virtual reality] provocation of OCD-related distress (VR provocation task).”[xxix] Such signals were used to identify when to deliver the therapeutic stimulation in order to counter the OCD symptoms. Thankfully, following the procedure and calibration the patient exhibited marked improvements in their OCD symptoms and recently shared her results publicly.[xxx] In both cases, there is a similar level of abductive justification for the efficacy of the delivered therapy. In the case study in which the patient was treated with adaptive deep brain stimulation, they at least had their neural activity tested in various settings to determine the optimum parameters for treatment to avoid them being based on guesswork. Additionally, the adaptive deep brain stimulation lead was already placed before the calibration trials were conducted, meaning that the patient had already taken on the bulk of the procedural risk before the efficacy could be determined. Such an efficacy test could have been replicated in the first patient’s cancer treatment, had it been biopsied and tested against the remaining immunotherapies in vitro. Yet, in the case of cancer with few options, one previous dose of a drug that appeared to work on the patient may justify further doses. However, as the Norwegian case presents, corroboration with known responses to a similar drug (from a clinical trial) could be helpful to validate the treatment strategy. (It should be noted that both patients were resigned to these last resort options regardless of the efficacy of treatment.) There are some elements of inductive logic seen with adaptive deep brain stimulation research in general. For example, abductively the focus could be that patient X’s stimulation parameters are different from patient Y’s and patient Z’s. In contrast, when grouped as subjects who obtained personalized stimulation, patients X, Y, and Z demonstrate an inductive aspect to this approach’s safety and/or efficacy. The OCD case holds plenty of abductive characteristics in line with precision medicine’s approach to treating cancer and as more individuals try the method, there will be additional data. With the gradual integration of AI into brain-computer interfaces in the name of efficacy, this reliance on abduction will continue, if not grow, over time. Moving forward, if a responsive deep brain stimulation treatment is novel and individualized (like the dose of nivolumab) and there is some other suggestion of efficacy (like clinical similarities to other patients in the literature), then it may justify insurance coverage for the investigative intervention, absent other unrelated reasons to deny it. III. Ethical Implications and Next Steps While AI’s use in oncology and neurology is not yet as prominent as its use in other fields (e.g., radiology), it appears to be on the horizon for both.[xxxi] AI can be found in both the functioning of the neurotechnologies as well as the implementation of precision medicine. The increasing use of AI may serve to further individualize both oncologic and neurological therapies. Given these implications and the handful of publications cited in this article, it is important to have a nuanced evaluation of how these treatments, which heavily rely on abductive justification, ought to be managed. The just use an abductive approach may be difficult as AI infused precision medicine is further pursued. At baseline, such technology relies on a level of advanced technology literacy among the general public and could exclude populations who lack access to basic technological infrastructure or know-how from participation.[xxxii] Even among nations with adequate infrastructure, as more patients seek out implantable neurotechnologies, which require robust healthcare resources, the market will favor patient populations that can afford this complex care.[xxxiii] If patients already have the means to pay for an initial dose/use of a precision medicine product out of pocket, should insurance providers be required to cover subsequent treatments?[xxxiv] That is, if a first dose of a cancer drug or a deep brain stimulator over its initial battery life is successful, patients may feel justified in having the costs of further treatments covered. The Norwegian patient’s experience implies there is a precedent for the idea that some public insurance companies ought to cover successful cancer therapies, however, insurance companies may not all see themselves as obligated to cover neurotechnologies that rely on personalized settings or that are based on precision/abductive research more than on clinical trials. CONCLUSION The fact that the cases outlined above rely on abductive style of reasoning implies that there may not be as strong a justification for coverage by insurance, as they are both experimental and individualized, when compared to the more traditional large clinical trials in which groups have the same or a standardized protocol (settings/doses). If a study is examining the efficacy of a treatment with a large cohort of patients or with different experimental groups/phases, insurance companies may conclude that the resulting symptom improvements are more likely to be coming from the devices themselves. A preference for inductive justification may take priority when ruling in favor of funding someone’s continued use of an implantable neurostimulator. There are further nuances to this discussion surrounding the classifications of these interventions as research versus clinical care that warrant future exploration, since such a distinction is more of a scale[xxxv] than binary and could have significant impacts on the “right-to-try” approach to experimental therapies in the United States.[xxxvi] Namely, given the inherent limitations of conducting large cohort trials for deep brain stimulation interventions on patients with neuropsychiatric disorders, surgically innovative frameworks that blend abductive and inductive methodologies, like with sham stimulation phases, have traditionally been used.[xxxvii] Similarly, for adaptive brain-computer interface systems, if there are no large clinical trials and instead only publications that demonstrate that something similar worked for someone else, then, in addition to the evidence that the first treatment/dose worked for the patient in question, the balance of reasoning would be valid and arguably justify insurance coverage. As precision approaches to neurotechnology become more common, frameworks for evaluating efficacy will be crucial both for insurance coverage and for clinical decision making. ACKNOWLEDGEMENT This article was originally written as an assignment for Dr. Francis Shen’s “Bioethics & AI” course at Harvard’s Center for Bioethics. I would like to thank Dr. Shen for his comments as well as my colleagues in the Lázaro-Muñoz Lab for their feedback. - [i] Jonathan Kimmelman and Ian Tannock, “The Paradox of Precision Medicine,” Nature Reviews. Clinical Oncology 15, no. 6 (June 2018): 341–42, https://doi.org/10.1038/s41571-018-0016-0. [ii] Henrik Vogt and Bjørn Hofmann, “How Precision Medicine Changes Medical Epistemology: A Formative Case from Norway,” Journal of Evaluation in Clinical Practice 28, no. 6 (December 2022): 1205–12, https://doi.org/10.1111/jep.13649. [iii] David Barrett and Ahtisham Younas, “Induction, Deduction and Abduction,” Evidence-Based Nursing 27, no. 1 (January 1, 2024): 6–7, https://doi.org/10.1136/ebnurs-2023-103873. [iv] Vogt and Hofmann, “How Precision Medicine Changes Medical Epistemology,” 1208. [v] Wireko Andrew Awuah et al., “Bridging Minds and Machines: The Recent Advances of Brain-Computer Interfaces in Neurological and Neurosurgical Applications,” World Neurosurgery, May 22, 2024, S1878-8750(24)00867-2, https://doi.org/10.1016/j.wneu.2024.05.104. [vi] Mark Riedl, “A Very Gentle Introduction to Large Language Models without the Hype,” Medium (blog), May 25, 2023, https://mark-riedl.medium.com/a-very-gentle-introduction-to-large-language-models-without-the-hype-5 f67941fa59e. [vii] David E. Burdette and Barbara E. Swartz, “Chapter 4 - Responsive Neurostimulation,” in Neurostimulation for Epilepsy, ed. Vikram R. Rao (Academic Press, 2023), 97–132, https://doi.org/10.1016/B978-0-323-91702-5.00002-5. [viii] Kimmelman and Tannock, 2018. [ix] Kimmelman and Tannock, 2018. [x] Simon Lohse, “Mapping Uncertainty in Precision Medicine: A Systematic Scoping Review,” Journal of Evaluation in Clinical Practice 29, no. 3 (April 2023): 554–64, https://doi.org/10.1111/jep.13789. [xi] Kimmelman and Tannock, “The Paradox of Precision Medicine.” [xii] Vogt and Hofmann, 1206. [xiii] Vogt and Hofmann, 1206. [xiv] Vogt and Hofmann, 1206. [xv] Vogt and Hofmann, 1207. [xvi] Vogt and Hofmann, 1207. [xvii] Vogt and Hofmann, 1207. [xviii] Vogt and Hofmann, 1210. [xix] Mehar Sahu et al., “Chapter Three - Artificial Intelligence and Machine Learning in Precision Medicine: A Paradigm Shift in Big Data Analysis,” in Progress in Molecular Biology and Translational Science, ed. David B. Teplow, vol. 190, 1 vols., Precision Medicine (Academic Press, 2022), 57–100, https://doi.org/10.1016/bs.pmbts.2022.03.002. [xx] Stefan Feuerriegel et al., “Causal Machine Learning for Predicting Treatment Outcomes,” Nature Medicine 30, no. 4 (April 2024): 958–68, https://doi.org/10.1038/s41591-024-02902-1. [xxi] Sunderland Baker et al., “Ethical Considerations in Closed Loop Deep Brain Stimulation,” Deep Brain Stimulation 3 (October 1, 2023): 8–15, https://doi.org/10.1016/j.jdbs.2023.11.001. [xxii] David Haslacher et al., “AI for Brain-Computer Interfaces,” 2024, 7, https://doi.org/10.1016/bs.dnb.2024.02.003. [xxiii] Burdette and Swartz, “Chapter 4 - Responsive Neurostimulation,” 103–4; “Premarket Approval (PMA),” https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpma/pma.cfm?id=P100026. [xxiv] Burdette and Swartz, “Chapter 4 - Responsive Neurostimulation,” 104. [xxv] Burdette and Swartz, 126. [xxvi] Sean L. Metzger et al., “A High-Performance Neuroprosthesis for Speech Decoding and Avatar Control,” Nature 620, no. 7976 (August 2023): 1037–46, https://doi.org/10.1038/s41586-023-06443-4. [xxvii] Hao Fang and Yuxiao Yang, “Predictive Neuromodulation of Cingulo-Frontal Neural Dynamics in Major Depressive Disorder Using a Brain-Computer Interface System: A Simulation Study,” Frontiers in Computational Neuroscience 17 (March 6, 2023), https://doi.org/10.3389/fncom.2023.1119685; Mahsa Malekmohammadi et al., “Kinematic Adaptive Deep Brain Stimulation for Resting Tremor in Parkinson’s Disease,” Movement Disorders 31, no. 3 (2016): 426–28, https://doi.org/10.1002/mds.26482. [xxviii] Young-Hoon Nho et al., “Responsive Deep Brain Stimulation Guided by Ventral Striatal Electrophysiology of Obsession Durably Ameliorates Compulsion,” Neuron 0, no. 0 (October 20, 2023), https://doi.org/10.1016/j.neuron.2023.09.034. [xxix] Nho et al. [xxx] Nho et al.; Erik Robinson, “Brain Implant at OHSU Successfully Controls Both Seizures and OCD,” OHSU News, accessed March 3, 2024, https://news.ohsu.edu/2023/10/25/brain-implant-at-ohsu-successfully-controls-both-seizures-and-ocd. [xxxi] Awuah et al., “Bridging Minds and Machines”; Haslacher et al., “AI for Brain-Computer Interfaces.” [xxxii] Awuah et al., “Bridging Minds and Machines.” [xxxiii] Sara Green, Barbara Prainsack, and Maya Sabatello, “The Roots of (in)Equity in Precision Medicine: Gaps in the Discourse,” Personalized Medicine 21, no. 1 (January 2024): 5–9, https://doi.org/10.2217/pme-2023-0097. [xxxiv] Green, Prainsack, and Sabatello, 7. [xxxv] Robyn Bluhm and Kirstin Borgerson, “An Epistemic Argument for Research-Practice Integration in Medicine,” The Journal of Medicine and Philosophy: A Forum for Bioethics and Philosophy of Medicine 43, no. 4 (July 9, 2018): 469–84, https://doi.org/10.1093/jmp/jhy009. [xxxvi] Vijay Mahant, “‘Right-to-Try’ Experimental Drugs: An Overview,” Journal of Translational Medicine 18 (June 23, 2020): 253, https://doi.org/10.1186/s12967-020-02427-4. [xxxvii] Michael S. Okun et al., “Deep Brain Stimulation in the Internal Capsule and Nucleus Accumbens Region: Responses Observed during Active and Sham Programming,” Journal of Neurology, Neurosurgery & Psychiatry 78, no. 3 (March 1, 2007): 310–14, https://doi.org/10.1136/jnnp.2006.095315. (shrink)

Evolutionary gradualism, the randomness of mutations, and the hypothesis that natural selection exerts a pervasive and substantial influence on evolutionary outcomes are pair-wise logically independent. Can the claims about selection and mutation be used to formulate an argument for gradualism? In his Genetical Theory of Natural Selection, R.A. Fisher made an important start at this project in his famous “geometric argument” by showing that a random mutation that has a smaller effect on two or more phenotypes will have a higher (...) average fitness than a random mutation that has a larger phenotypic effect. Motoo Kimura’s demonstration that a gene’s probability of fixation depends on both the selection coefficient and the effective population size shows that Fisher’s argument for gradualism was mistaken. Here we analyze Fisher’s argument and explain how Kimura’s theory leads to a conclusion that Fisher did not anticipate. We identify a fallacy that reasoning about fitness differences and their evolutionary consequences should avoid. We then distinguish forward-directed from backward-directed versions of gradualism. The backward-directed thesis about a single mutation may be correct, but the forward-directed thesis is not. After that we consider a sequence of random mutations that all affect the same cluster of phenotypes and Allen Orr’s idea that there is an optimal sequence of mutation sizes, moving from larger to smaller as the population approaches a fixed optimum. This provides a likelihood justification for a forward-directed version of gradualism when there is a fixed optimum, but it also provides an argument against forward-directed gradualism if the optimum shifts substantially as the population evolves. Finally, we consider whether genome-wide association studies (GWASs) can furnish empirical evidence that bears on the truth of gradualism. The version of gradualism that GWASs directly bear on concerns the phenotypic effect size of a gene after it arises by mutation and has reached an appreciable frequency, not the phenotypic size of the mutation event itself. (shrink)

Historians of science have long been agreeing: what many textbooks of evolutionary biology say, about the histories of Darwinism and the New Synthesis, is just too simple to do justice to the complexities revealed to critical scholarship and historiography. There is no current consensus, however, on what grand narratives should replace those textbook histories. The present paper does not offer to contribute directly to any grand, consensual, narrational goals; but it does seek to do so indirectly by showing how, in (...) just one individual case, details of intellectual biography connect with big picture issues. To this end, I examine here how very diverse scientific and metaphysical commitments were integrated in Sewall Wright’s own personal synthesis of biology and philosophy. Taking as the decisive text the short final section of Wright’s long 1931 paper on ‘Evolution in Mendelian populations,’ I examine how his shifting balance theory related to his optimum breeding strategy research, his physiological genetics, his general theory of homogenising and heterogenesing causation and his panpsychist view of mind and matter; and I discuss how understanding these relations can clarify Wright’s place in the longue durée of evolutionary thought. (shrink)

This work proposes a hybrid heuristic algorithm to solve the bus rapid transit intelligent scheduling problem, which is a combination of the genetic algorithm, simulated annealing algorithm, and fitness scaling method. The simulated annealing algorithm can increase the local search ability of the genetic algorithm, so as to accelerate its convergence speed. Fitness scaling can reduce the differences between individuals in the early stage of the algorithm, to prevent the genetic algorithm from falling into a local optimum through increasing (...) the diversity of the population. It can also increase the selection probability of outstanding individuals, and speed up the convergence at the late stage of the algorithm, by increasing the differences between individuals. Using real operational data of BRT Line 1 in a city of Zhejiang province, the new scheduling scheme can be obtained through algorithm simulation. The passengers’ total waiting time in a single way will be reduced by 40 h on average under the same operating cost compared with the original schedule scheme in a day. (shrink)

We propose a new Real-coded GA(RCGA) using the combination of two crossovers, UNDX-m and EDX. The search region of UNDX-m is biased to the inside area that the population of the RCGA covers. Because of this search bias, the GA using UNDX-m causes stagnation of its search if the cost function has a kind of structure, so called, a ridge structure or a multiple-peak structure. In order to overcome this stagnation, we propose a new crossover EDX, whose search is (...) biased toward extrapolative one. Experimental results show that RCGA with EDX can deal with both ridge-structure function whose dimension reaches more than hundreds and multiple-peak function whose optimum resides at the corner of the search area. (shrink)

Under the background of the information age, scientific research and engineering practice have developed vigorously, resulting in many complex optimization problems that are difficult to solve. How to design more effective optimization methods has become the focus of urgent solutions in many academic fields. Under the guidance of such demand, intelligent optimization algorithms have emerged. This article analyzes and optimizes the modern artificial intelligence teaching information system in detail. On the basis of determining the network architecture, a detailed demand analysis (...) was carried out, and the overall structure optimization of the network was given; the business process and data flow of the main modules of the website were optimized. In order to further enhance the local search ability of the algorithm, a multiclass interactive optimization algorithm is proposed in combination with the Euclidean distance-based clustering method, which changes the teaching mode from “one-person teaching” to “multiperson teaching.” This clustering method has lower complexity and is beneficial to enhance the utilization of neighborhood information. At the same time, in order to enhance the diversity of the population and strengthen the connection between the subgroups, after the teaching phase, the worst students in each subgroup are allowed to learn from the best teachers of the population, and after the learning phase, individuals in a random subgroup are allowed to learn from other subgroups. The algorithm was tested in the experimental environment of unconstrained, constrained, and an engineering problem. From the test results, it can be seen that the algorithm is not easy to fall into the local optimum. Compared with other algorithms, the solution accuracy is higher and the stability is better. And it performed well in engineering optimization problems, thus verifying the effectiveness of the strategy. (shrink)

Particle Swarm Optimization is an excellent population-based optimization algorithm. Meanwhile, because of its inspiration source and the velocity update feature, it is also widely used in the collaborative searching tasks for swarm robotics. One of the PSO-based models for robotic swarm searching tasks is Robotic PSO. It adds additional items for obstacle avoidance into standard PSO and has been applied to many single-target search tasks. However, due to PSO’s global optimization characteristics, it is easy to converge to a specific (...) position in the search space and lose the ability to explore further. When faced with the problem of multitarget searching, it may become inefficient or even invalid. This paper proposes an Exploration Enhanced Robotic PSO method for multitarget searching problems for robotic swarms. The proposed method modifies the third item in the RPSO as an additional attraction term. This item not only enables the robot to avoid collisions but also guides the swarm to search unexplored regions as much as possible. This operation increases the swarm’s task-specific diversity, making the system cover a broader search area and avoid falling into local optimums. Besides, the aggregation degree and evolution speed factors are also included in determining the inertia weight of the proposed method, which adjusts the swarm’s internal diversity dynamically. The comparison results show that this method can balance the relationship between exploration and exploitation well, which has the potential to be applied to multitarget searching scenarios. (shrink)

Aiming at the shortcomings of standard particle swarm optimization algorithms that easily fall into local optimum, this paper proposes an optimization algorithm that improves quantum behavioral particle swarms. Aiming at the problem of premature convergence of the particle swarm algorithm, the evolution speed of individual particles and the population dispersion are used to dynamically adjust the inertia weights to make them adaptive and controllable, thereby avoiding premature convergence. At the same time, the natural selection method is introduced into (...) the traditional position update formula to maintain the diversity of the population, strengthen the global search ability of the LTQPSO algorithm, and accelerate the convergence speed of the algorithm. The improved LTQPSO algorithm is applied to landscape trail path planning, and the research results prove the effectiveness and feasibility of the algorithm. (shrink)

We present a quantitative model of sex allocation to investigate whether the simple “rules of thumb” suggested by Trivers and Willard (1973) would really maximize numbers of grandchildren in human populations. Using demographic data from the !Kung of southern Africa and the basic assumptions of the Trivers-Willard hypothesis, we calculate expected numbers of grandchildren based on age- and sex-specific reproductive value. Patterns of parental investment that would maximize numbers of expected grandchildren often differ from the Trivers-Willard rules. In particular, the (...) optimum parental behavior is sensitive to population dynamics, type of parental investment, and, most important, relative ages of sons and daughters. It is doubtful whether a parent blindly following the simple Trivers-Willard rules would maximize numbers of expected grandchildren, on average. In addition, we show that sex-specific infanticide will almost never achieve the goal of maximizing expected numbers of grandchildren. (shrink)

The travelling salesman problem (TSP) belongs to the class of NP-hard problems, in which an optimal solution to the problem cannot be obtained within a reasonable computational time for large-sized problems. To address TSP, we propose a hybrid algorithm, called GA-TCTIA-LBSA, in which a genetic algorithm (GA), tour construction and tour improvement algorithms (TCTIAs) and a list-based simulated annealing (LBSA) algorithm are used. The TCTIAs are introduced to generate a first population, and after that, a search is continued with (...) the GA. The problem of premature convergence of the GA to local optimum is tackled by a method called social disaster technique. Afterwards, the LBSA is applied to generate a new population based on one of two proposed operators called packing and judgement day. The proposed algorithm is implemented in the MATLAB environment, and its two variants, called GA-TCTIA-LBSA packing and GA-TCTIA-LBSA judgement day, are tested on symmetric and asymmetric instances from TSPLIB. The overall results demonstrate that the proposed GA-TCTIA-LBSAs offer promising results, particularly for small-sized instances. (shrink)

Conventional theory assumes that economic agents perform at optimal levels of efficiency by definition and this is achieved when individuals behave in a particular fashion. Moreover, neoclassical production theory masks the process by which optimal output can be achieved. I argue that economic theory should be revised to incorporate some key findings of behavioural economics, while retaining the conventional theory’s normative ideal of optimum output whilst rejecting its normative procedural ideals of how to achieve optimality in production. I argue (...) that neoclassical procedures can be expected to yield sub-optimal levels of output and therefore should not be benchmarks for procedural rationality. I present an alternative more realistic and analytically precise specification of the production function related to the fast and frugal heuristics narrative pioneered by Gigerenzer and Leibenstein’s x-efficient theory. This approach incorporates an understanding of the appropriate procedures, psychological and organization variables, decision-making capabilities and end-goals required to achieve optimality in production and, thereby, grow the wealth of nations, thereby enhancing the material wellbeing of the population at large. This also provides us with the tools to better identify economic inefficiency and the conditions that contribute to it. (shrink)

The objective of this study was to isolate endophytic bacteria from roots of Brachiaria humidicola cv. humidicola (Rendle) Schweick and to relate their presence to pH, organic matter and phosphorus contents of the soil of cattle farms located in the municipality of San Benito Abad. Soil sampling was carried out with roots of B. humicola for the isolation and counting of the population density of endophytic bacteria and soil samples were also collected for the determination of pH, organic matter (...) and phosphorus parameters. The results found indicate that there is an amount of endophytic bacteria in roots of B. humidicola when the soil contains optimum pH values of (6.1 ± 6.98); low to moderate phosphorus content (10.8 ± 16.28 mg/kg) and low to moderate organic matter content (1.7 ± 2.31%). The presence of endophytic bacteria was observed in a range of 3.0 ± 8.0 X 106 CFU/g of roots. There is a worldwide need to establish a relationship between endophytic bacteria and soil physical-chemical quality indicator parameters to predict a change in functional diversity under physical, chemical and biological conditions of the soil ecosystem. (shrink)

The basic reproduction ratio, R0, is a fundamental concept in epidemiology. It is defined as the total number of secondary infections brought on by a single primary infection, in a totally susceptible population. The value of R0 indicates whether a starting epidemic reaches a considerable part of the population and causes a lot of damage, or whether it remains restricted to a relatively small number of individuals. To calculate R0 one has to evaluate an integral that ranges over (...) the duration of the infection of the host. This duration is, of course, limited by remaining host longevity. So, R0 depends on remaining host longevity and in this paper we show that for long-lived hosts this aspect may not be ignored for long-lasting infections. We investigate in particular how this epidemiological measure of pathogen fitness depends on host longevity. For our analyses we adopt and combine a generic within- and between-host model from the literature. To find the optimal strategy for a pathogen from an evolutionary point of view, we focus on the indicator $$R_0^{{opt}}$$, i.e., the optimum of R0 as a function of its replication and mutation rates. These are the within-host parameters that the pathogen has at its disposal to optimize its strategy. We show that $$R_0^{{opt}}$$ is highly influenced by remaining host longevity in combination with the contact rate between hosts in a susceptible population. In addition, these two parameters determine whether a killer-like or a milker-like strategy is optimal for a given pathogen. In the killer-like strategy the pathogen has a high rate of reproduction within the host in a short time span causing a relatively short disease, whereas in the milker-like strategy the pathogen multiplies relatively slowly, producing a continuous small amount of offspring over time with a small effect on host health. The present research allows for the determination of a bifurcation line in the plane of host longevity versus contact rate that forms the boundary between the milker-like and killer-like regions. This plot shows that for short remaining host longevities the killer-like strategy is optimal, whereas for very long remaining host longevities the milker-like strategy is advantageous. For in-between values of host longevity, the contact rate determines which of both strategies is optimal. (shrink)

From the end of the First World War, a broad discussion took place within the framework of the revived German constitutional teaching on the question of the physical normality of man. The founder of the so-called statistical concept of normality, which preceded the still widespread normal (reference) interval concept, is H. Rautmann, who gave it the character of a tool for discriminating between health and disease. Among some of his successors (Bauer, Borchardt, Günther), however, it was considered more a means (...) of establishing a type, without supposing any precise relation between the frequency of a character in the population and the probability of the occurrence of disease. The concept of a statistical norm as a certain region of the variation range of a character determined by the parameters of Gaussian distribution was criticized both by the supporters of the ideal norm (Hildebrandt) and those who were in favour of a ‘personal’ norm (Grote). The underlying motifs of these three conceptions of normality influenced German constitutional doctrine until after the end of the Second World War, but without a satisfactory solution to the diagnosis of physical normality being found. Since the 1950s, world medicine has moved more and more in the direction of prevention, with the emphasis on a study of individual dispositions to disease and its precursors. In this connection a new view of health has gained importance whereby it is considered a smoothly gradated condition, not sharply distinguished from disease (‘continual’ model of health and disease as opposed to the previous ‘alternative’ model). The purpose of diagnostic characters is no longer merely to place patients in clearly defined categories as healthy or affected by one disease or another, but has taken on the function of indices of the disposition to disease among those who exhibit ‘gross normality’. Discrimination between the alternative and continuous models allows a clarification to be made of the sources of the confusion in which the pre-war concept of statistical normality had found itself. Today many exceptions are known to the rule that the functional optimum lies in the region of the population mean, both for the population as a whole and for individuals; and immense variability has been found in the manner in which individuals in the population attain health. Thus a distinction between health and disease by statistical means alone (such as establishing some sort of species design) is not possible at all. The ideal of a personal norm is pursued today through the concept of a multivariate norm backed up by modern data processing methods, though it was anticipated in principle by Kaup even in the 1920s. CiteULike Connotea Del.icio.us What's this? (shrink)

From approximately 900 to 1300 a.d., a period known to climatologists and historians of science as the Little Climatic Optimum, temperatures in the Northern Hemisphere averaged one or two degrees Fahrenheit above normal—this according to ice‐core samples, tree ring analysis, the calculation of sea levels, and other standards of measurement. In what would become known as the Four Corners region of the United States, the culture of the Anasazi flourished as never before in the now‐famous ruins of such magnificent (...) cliff dwellings as Chaco Canyon. Meanwhile, far to the north, the Viking raider and convicted killer Eric the Red brought European civilization by open boat to Greenland, so named to attract wary settlers whose common sense dictated that these harsh surroundings might spell their doom. Yet both cultures would flourish for upward of three hundred years.Things began to change for the worse in the latter half of the thirteenth century, as shifts in wind and weather ushered in the so‐called Little Ice Age, which lasted from about 1300 to 1850. Brian Fagan, a professor of archaeology at the University of California at Santa Barbara and the author of more than a dozen books, most of which are directed at the general reader, observes this period through the lens of climate change, with particular emphasis on what transpired in an anxious and often turbulent Europe.From 1300 onward the climate grew cooler, more stormy, and subject to sporadic extremes—in a word, unpredictable. Glaciers and pack ice advanced; rivers never known to freeze over became natural skating rinks; blizzards enveloped and erased the frozen landscape; and people starved and froze to death in the seemingly endless winters depicted by the Flemish master Peter Brueghel. At other times the climatic seesaw drove temperatures up, replacing bitter cold with blazing summers, drought, or torrential rains, changes that could take place in a single season or across decades. In between there were long periods of mild winters and warm summers that saw the harvesting of bountiful crops. But overall temperatures in the Northern Hemisphere declined, boosting the misery index of Europeans left to wonder what they had done to so offend an angry God.Unlike the current greenhouse warming ushered in by the Industrial Revolution, the climatic variability of the Little Ice Age remains, in Fagan's words, “a conundrum.” He speculates that it may have had much to do with a shift in the great ocean conveyor belt that rushes, like a thousand Amazons, from Southern Hemisphere to Northern and back again. Or it may be associated with the virtual disappearance of sunspots during much of the period under scrutiny, or with some other phenomenon that we know much too little about.The scientific causes aside, the author takes great pains to disassociate himself from what he calls “environmental determinism,” the notion that climate change has been a primary trigger for major historical events or that it has been the single most important cause of any civilization's decline and fall. Rather, he sees it as one of many factors, including politics, war, religion, and population shifts, that scholars must fold into their teaching of history and related subjects. This may be so in many instances, but how else to explain the literal overnight disappearance of the Anasazi from the Chaco, where the ashes from their fires of six hundred years ago lie scattered on the floor? Then there are the haunting words of Ivar Bardarson, a seafaring Norwegian priest who, in 1361, sailed up Greenland's west coast, hoping to make contact with his fellow Christians, from whom nothing had been heard for several years because of the ice. Search though they did, Bardarson and his companions found no survivors, causing the priest to remark: “There was never a man.”This well‐written and copiously illustrated book will make excellent reading for generalist and professional alike. And for those wishing to introduce the subject of climate change to undergraduates by placing it within a historical context, The Little Ice Age offers an excellent place to start. (shrink)

This book is a comprehensive and unique text and reference in medical ethics. By far the most inclusive set of primary documents and articles in the field ever published, it contains over 100 selections. Virtually all pieces appear in their entirety, and a significant number would be difficult to obtain elsewhere. The volume draws upon the literature of history, medicine, philosophical and religious ethics, economics, and sociology. A wide range of topics and issues are covered, such as law and medicine, (...) truth-telling by the physician, research, population policy, genetics, abortion, dying, and individual rights in medical care. The selections span the centuries, beginning with material from the works of Hippocrates, continuing through Thomas Percival, John Stuart Mill, and Claude Bernard, down to modern commentators like Henry K. Beecher, Walsh McDermott, David L. Bazelon, Paul Freund, H. L. A. Hart, John Rawls, Paul Ramsey, Richard McCormick, Rashi Fein, and Bernard Barber. The text has eight major divisions, beginning with sections on the ethical dimensions of the physician-patient relationship in history; the moral bases of medical ethics; and regulation, compulsion, and protection of the consumer in clinical medicine and public health. Each of these sections includes key essays that appear for the first time. All of the book's major divisions contain primary documents: codes such as the Hippocratic Oath, Medieval Law for the Regulation of Medicine, and the first as well as the most recent code of the American Medical Association; court decisions, including those on Karen Quinlan and on abortion in the United States and West Germany; government documents such as the statement of the National Commission on the Protection of Human Subjects, the Tuskegee Syphilis Report, the British Parliamentary debate on euthanasia, and the Council of Europe on rights of the sick and dying; and various published guidelines such as the Harvard Medical School brain death criteria, the American Hospital Association on patient's rights, and Pope Pius XII on the prolongation of life. Cases that illustrate moral dilemmas are provided for discussion purposes. Each section is preceded by a succinct editor's introduction. The documents and essays are of practical value for practitioners and students in medicine, law, ethics, and counselling, and for individual patients and groups concerned with medical care. Through encompassing divergent viewpoints, the essays and primary documents were selected to encourage humane practices and deepen understanding of the multiple traditions that shaped and do shape the development of medicine. (shrink)

Various results show the ‘formal equivalence’ of kin and group selectionist methodologies, but this does not preclude there being a real and useful distinction between kin and group selection processes. I distinguish individual- and population-centred approaches to drawing such a distinction, and I proceed to develop the latter. On the account I advance, the differences between kin and group selection are differences of degree in the structural properties of populations. A spatial metaphor provides a useful framework for thinking about (...) these differences: kin and group selection may be conceptualized as large, overlapping regions of K - G space. I then consider some implications of the account, defend it from possible objections, and further argue that the structural features characteristic of both kin and group selection may recur at multiple levels of biological organization. (shrink)

We identify a novel ‘cultural red king effect’ that, in many cases, results in stable arrangements which are to the detriment of minority groups. In particular, we show inequalities disadvantaging minority groups can naturally arise under an adaptive process when minority and majority members must routinely determine how to divide resources amongst themselves. We contend that these results show how inequalities disadvantaging minorities can likely arise by dint of their relative size and need not be a result of either explicit (...) nor implicit prejudices, nor due to intrinsic differences between minority and majority members. (shrink)

Ecologist Richard Levins argues population biologists must trade‐off the generality, realism, and precision of their models since biological systems are complex and our limitations are severe. Steven Orzack and Elliott Sober argue that there are cases where these model properties cannot be varied independently of one another. If this is correct, then Levins's thesis that there is a necessary trade‐off between generality, precision, and realism in mathematical models in biology is false. I argue that Orzack and Sober's arguments fail (...) since Levins's thesis concerns the pragmatic features of model building not just the formal properties of models. (shrink)

Ernst Mayr's typological/population distinction is a conceptual thread that runs throughout much of his work in systematics, evolutionary biology, and the history and philosophy of biology. Mayr himself claims that typological thinking originated in the philosophy of Plato and that population thinking was first introduced by Charles Darwin and field naturalists. A more proximate origin of the typological/population thinking, however, is found in Mayr's own work on species. This paper traces the antecedents of the typological/population distinction (...) by detailing Mayr's changing views of species between 1942 and 1955. During this period, Mayr struggles to refine the biological species concept in the face of tensions that exist between studying species locally and studying them as geographically distributed collections of variable populations. The typological/population distinction is first formulated in 1955, when Mayr generalizes from the type concept versus the population concept in taxonomy to typological versus population thinking in biology more generally. Mayr's appeal to the more general distinction between typological and population thinking coincides with the waning status of natural history and evolutionary biology that occurs in the early 1950s and the distinction plays an important role in Mayr's efforts to legitimate the natural historical sciences. (shrink)

Homeostatic Property Cluster (HPC) theory suggests that species and other biological taxa consist of organisms that share certain similarities. HPC theory acknowledges the existence of Darwinian variation within biological taxa. The claim is that “homeostatic mechanisms” acting on the members of such taxa nonetheless ensure a significant cluster of similarities. The HPC theorist’s focus on individual similarities is inadequate to account for stable polymorphism within taxa, and fails properly to capture their historical nature. A better approach is to treat distributions (...) of traits in species populations as irreducible facts, explained in terms of selection pressures, genealogy, and other evolutionary factors. We call this view Population Structure Theory (PST). PST accommodates the view, implicit in biological systematics, that species are identified by reference to particular historical populations. (shrink)

Advances in technology have made it possible for us to take actions that affect the numbers and identities of humans and other animals that will live in the future. Effective and inexpensive birth control, child allowances, genetic screening, safe abortion, in vitro fertilization, the education of young women, sterilization programs, environmental degradation and war all have these effects. Although it is true that a good deal of effort has been devoted to the practical side of population policy, moral theory (...) has not dealt adequately with the new possibilities. The dilemma faced by moral theory is that traditional theories cannot answer moral questions involving the creation of people. Two related problems arise. The first concerns numbers: how many people should there be? The second asks what sort of people should live and what their levels of well-being should be. Conventional social-contract theories, including the work of Rawls (1971), are restricted to situations with a fixed number of individuals. Sumner (1978) attempts to extend a Rawlsian veil-of-ignorance approach to possible people but is aware of the difficulties involved. The main problem is that possible people must be thought to benefit when they move from non-existence to existence, a view that we reject (see Section 1, Heyd, 1992, Chapter 1; McMahan, 1996a; Parfit, 1984, Appendix G). Rights-based and duty-based theories suffer from a similar problem; there must be a person who has the right or a person to whom the duty is owed (see McMahan, 1981). (shrink)

I define a concept of causal probability and apply it to questions about the role of probability in evolutionary processes. Causal probability is defined in terms of manipulation of patterns in empirical outcomes by manipulating properties that realize objective probabilities. The concept of causal probability allows us see how probabilities characterized by different interpretations of probability can share a similar causal character, and does so in such way as to allow new inferences about relationships between probabilities realized in different chance (...) setups. I clarify relations between probabilities and properties defined in terms of them, and argue that certain widespread uses of computer simulations in evolutionary biology show that many probabilities relevant to evolutionary outcomes are causal probabilities. This supports the claim that higher-level properties such as biological fitness and processes such as natural selection are causal properties and processes, contrary to what some authors have argued. (shrink)