Concepts of Drift and Selection in “The Great Snail Debate” of the 1950s and Early 1960s

Recently, much philosophical discussion has centered on the best way to characterize the concepts of random drift and natural selection, and, in particular, on the question of whether selection and drift can be conceptually distinguished (Beatty 1984; Brandon 2005; Hodge 1983, 1987; Millstein 2002, 2005; Pfeifer 2005; Shanahan 1992; Stephens 2004). These authors all contend, to a greater or lesser degree, that their concepts make sense of biological practice. So, it should be instructive to see how the concepts of drift and selection were distinguished by the disputants in a high-profile debate; debates such as these often force biologists to take a more philosophical turn, discussing the concepts at issue in greater detail than usual. A prime candidate for just such a case study is what William Provine (1986) has termed “The Great Snail Debate,” that is, the debate over the highly polymorphic land snails Cepaea nemoralis and Cepaea hortensis in the 1950s and early 1960s. This study will reveal that much of the present-day confusion over the concepts of drift and selection is rooted in confusions of the past. Nonetheless, there are lessons that can be learned about nonadaptiveness, indiscriminate sampling, and causality with respect to these two concepts. In particular, this paper will shed light on the following questions: 1) What is “drift”? Is “drift” a purely mathematical construct, a physical process analogous to the indiscriminate sampling of balls from an urn, or the outcome of a sampling process? 2) What is “nonadaptiveness,” and is a proponent of drift committed to claims that organisms’ traits are nonadaptive? 3) Can disputes concerning selection and drift be settled by statistics alone, or is causal information essential? If causal information is essential, what does that say about the concepts of “drift” and “selection” themselves

Evaluating the economic return to public wind energy research and development in the United States

The U.S. government has invested in wind energy research since 1976. Building on a literature that has sought to develop and apply methods for retrospective benefit-to-cost evaluation for federal research programs, this study provides a quantitative analysis of the economic social return on these historical wind energy research investments. Importantly, the study applies multiple innovative methods and varies important input parameters to test the sensitivity of the results. The analysis considers public wind research expenditures and U.S. wind power deployment over the period 1976–2017, while also accounting for the full useful lifetime of wind projects built over this period. Assessed benefits include energy cost savings and health benefits due to reductions in air pollution. Overall, this analysis demonstrates sizable, positive economic returns on past wind energy research. Under the core analysis and with a 3% real discount rate, the net benefits from historical federal wind energy research investments are found to equal $31.4 billion, leading to an 18 to 1 benefit-to-cost ratio and an internal rate of return of 15.4%. Avoided carbon dioxide emissions are not valued in monetary terms, but are estimated at 1510 million metric tons. Alternative methods and input assumptions yield benefit-to-cost ratios that fall within a relatively narrow range from 7-to-1 to 21-to-1, reinforcing in broad terms the general finding of a sizable positive return on investment. Unsurprisingly, results are sensitive to the chosen discount rate, with higher discount rates leading to lower benefit-to-cost ratios, and lower discount rates yielding higher benefit-to-cost ratios

Generating and Sampling Orbits for Lifted Probabilistic Inference

A key goal in the design of probabilistic inference algorithms is identifying and exploiting properties of the distribution that make inference tractable. Lifted inference algorithms identify symmetry as a property that enables efficient inference and seek to scale with the degree of symmetry of a probability model. A limitation of existing exact lifted inference techniques is that they do not apply to non-relational representations like factor graphs. In this work we provide the first example of an exact lifted inference algorithm for arbitrary discrete factor graphs. In addition we describe a lifted Markov-Chain Monte-Carlo algorithm that provably mixes rapidly in the degree of symmetry of the distribution

Symbolic Exact Inference for Discrete Probabilistic Programs

The computational burden of probabilistic inference remains a hurdle for applying probabilistic programming languages to practical problems of interest. In this work, we provide a semantic and algorithmic foundation for efficient exact inference on discrete-valued finite-domain imperative probabilistic programs. We leverage and generalize efficient inference procedures for Bayesian networks, which exploit the structure of the network to decompose the inference task, thereby avoiding full path enumeration. To do this, we first compile probabilistic programs to a symbolic representation. Then we adapt techniques from the probabilistic logic programming and artificial intelligence communities in order to perform inference on the symbolic representation. We formalize our approach, prove it sound, and experimentally validate it against existing exact and approximate inference techniques. We show that our inference approach is competitive with inference procedures specialized for Bayesian networks, thereby expanding the class of probabilistic programs that can be practically analyzed

Can you shut the door behind you?

Can you shut the door behind you? creates a parallel between the basement and the subconscious. These settings (one mental and one physical) serve as storage units. In creating these spaces, I became fascinated with the container as a sculptural form; objects whose purpose is to carry and cradle other objects. Pipes cycling water throughout the home, crates and boxes holding family memorabilia, washing machines continuously cycling dirty laundry. My work captures how these containers, abandoned in this forgotten space, grow and decay. The entire space is in and of itself a constructed container a viewer may enter. Casting is an integral method in the production of my work and allows me to illustrate the function of the container. Rather than fabricating my own molds, I pour or paint material onto found objects. The found objects become the molds themselves. This process captures the vacant, forgotten spaces within them. “Can you shut the door behind you?” halts the cyclical functions of the basement and of the subconscious. It allows one to examine the mechanism as a whole. In this process, I began to question to function of the basement. Although it is a space used to store and archive, its organization is rooted in chaos; it is space for things we want to keep, but can’t look at. It possesses a facade of order. It contains a history of detritus. It is constantly expanding, contracting, and shifting below our feet. Like the subconscious, this space is both logical and illogical, constructed and organic, stable and fragile. It presents comforting and familiar forms, but works within an unfamiliar system; outlets and pipes made out of plaster leading to an unknown place, the underside of a bath with no floor to hold it up, and rubber crates too weak to support themselves. These sculptures compose this complex system, yet they are also the reasons it is decaying. Nate Millstein, 201

When routine screening is not routine : Preparing patients for the unexpected

In our current environment of value based care and payment models, greater emphasis is placed on completing evidence based, routine screening tests for patients. While there is clear preventive health benefit, population based initiatives may overlook opportunities to prepare individual patients for possible abnormal results. Efforts to manage expectations, address health literacy gaps and ensure emotional support may help limit unnecessary distress and suffering during the screening process

How Does Wind Project Performance Change with Age in the United States?

Wind-plant performance declines with age, and the rate of decline varies between regions. The rate of performance decline is important when determining wind-plant financial viability and expected lifetime generation. We determine the rate of age-related performance decline in the United States wind fleet by evaluating generation records from 917 plants. We find the rate of performance decline to be 0.53%/year for older vintages of plants and 0.17%/year for newer vintages of plants on an energy basis for the first 10 years of operation, which is on the lower end of prior estimates in Europe. Unique to the United States, we find a significant drop in performance by 3.6% after 10 years, as plants lose eligibility for the production tax credit. Certain plant characteristics, such as the ratio of blade length to nameplate capacity, influence the rate of performance decline. These results indicate that the performance decline rate can be partially managed and influenced by policy

Evolution

This paper is an overview of the philosophy of evolution past, present, and future to be published in Blackwell's Guide to the Philosophy of Science, edited by P.K. Machamer and M. Silberstein. It surveys the following topics: the neutralist/selectionist debate, the adapationist programme and its challenges, sociobiology, contingency, laws of biology, the species category problem, the species taxon problem, the tautology problem, fitness, units of selection