Satellite communications: the political determination of technological development, 1961-1975

The thesis sets forth a model relating political contention to technological development. The selective realisation of a technical potentiality is shown to have been determined by conflict and negotiation among shifting alliances of state and private-industrial entities, each attempting to impose its requirements upon an emergent technology and thereby to dictate the precise form and pace of technical development. The 'course of communications satellite development is examined during the technology's formative period from 1961 to 1975--as the product of struggles over technological control. Negotiation centered upon control, and contending modes of technical development were promoted and opposed on the basis of their perceived consequences upon the distribution of effective control over the technology. The initial mode of satellite development lasted from 1961 to 1971 and is characterised as pre-emptive underdevelopment; urgency and haste were combined with tight constraints on the qualitative breadth allowed to technological articulation. Pre-emptive underdevelopment derived from an uneasy political accommodation struck among constituencies dominant during this phases the U.S. government, American communications carrier industry and a Western European intergovernmental bloc. The reigning compromise was directed toward expediting satellite development sufficiently to forestall rival deployments without endangering existing and anticipated interests in both satellite and competitive technologies. Technical development beneath a minimum level risked undermining the regime of control by leaving open the possibility of rival satellite systems; but development beyond a maximum level would have harmed the outstanding industrial and political interests in whose defence control was sought, while subverting the control regime by widening the legitimate scope for multinational participation in authority over the technology. Pre-emptive underdevelopment, it is argued, was succeeded largely by the products of its own success in meeting the policy requirements of initially dominant entities and in thus reducing the continued importance of satellite technology as a political arena and instrumentality. Restraints upon development could therefore, in the post-1971 period, be relaxed, while the growing demand for a wider array of satellite services encouraged emergence of a more intensive mode of technological development under the auspices of a de-cartelised, quasi-federal and multinational political regime

Conservative Inference for Counterfactuals

In causal inference, the joint law of a set of counterfactual random variables is generally not identified. We show that a conservative version of the joint law - corresponding to the smallest treatment effect - is identified. Finding this law uses recent results from optimal transport theory. Under this conservative law we can bound causal effects and we may construct inferences for each individual's counterfactual dose-response curve. Intuitively, this is the flattest counterfactual curve for each subject that is consistent with the distribution of the observables. If the outcome is univariate then, under mild conditions, this curve is simply the quantile function of the counterfactual distribution that passes through the observed point. This curve corresponds to a nonparametric rank preserving structural model

Crows Spontaneously Exhibit Analogical Reasoning

SummaryAnalogical reasoning is vital to advanced cognition and behavioral adaptation. Many theorists deem analogical thinking to be uniquely human and to be foundational to categorization, creative problem solving, and scientific discovery [1]. Comparative psychologists have long been interested in the species generality of analogical reasoning, but they initially found it difficult to obtain empirical support for such thinking in nonhuman animals (for pioneering efforts, see [2, 3]). Researchers have since mustered considerable evidence and argument that relational matching-to-sample (RMTS) effectively captures the essence of analogy, in which the relevant logical arguments are presented visually [4]. In RMTS, choice of test pair BB would be correct if the sample pair were AA, whereas choice of test pair EF would be correct if the sample pair were CD. Critically, no items in the correct test pair physically match items in the sample pair, thus demanding that only relational sameness or differentness is available to support accurate choice responding. Initial evidence suggested that only humans and apes can successfully learn RMTS with pairs of sample and test items [4–7]; however, monkeys have subsequently done so [8–12]. Here, we report that crows too exhibit relational matching behavior. Even more importantly, crows spontaneously display relational responding without ever having been trained on RMTS; they had only been trained on identity matching-to-sample (IMTS). Such robust and uninstructed relational matching behavior represents the most convincing evidence yet of analogical reasoning in a nonprimate species, as apes alone [7] have spontaneously exhibited RMTS behavior after only IMTS training

The Evolution of Best Practices with High Performance Steel for Bridges

High Performance Steel, grade 70 (HPS-70W) became available for use in early 1996 for fabrication and testing in bridges. Two (2) states, Nebraska and Tennessee agreed to be the first to implement usage. This paper provides a discussion of 3 Tennessee case histories in which high performance steel has been used to achieve weight and cost economies

Associative Concept Learning in Animals

Nonhuman animals show evidence for three types of concept learning: perceptual or similarity-based in which objects/stimuli are categorized based on physical similarity; relational in which one object/stimulus is categorized relative to another (e.g., same/different); and associative in which arbitrary stimuli become interchangeable with one another by virtue of a common association with another stimulus, outcome, or response. In this article, we focus on various methods for establishing associative concepts in nonhuman animals and evaluate data documenting the development of associative classes of stimuli. We also examine the nature of the common within-class representation of samples that have been associated with the same reinforced comparison response (i.e., many-to-one matching) by describing manipulations for distinguishing possible representations. Associative concepts provide one foundation for human language such that spoken and written words and the objects they represent become members of a class of interchangeable stimuli. The mechanisms of associative concept learning and the behavioral flexibility it allows, however, are also evident in the adaptive behaviors of animals lacking language

Causal Effect Estimation after Propensity Score Trimming with Continuous Treatments

Most works in causal inference focus on binary treatments where one estimates a single treatment-versus-control effect. When treatment is continuous, one must estimate a curve representing the causal relationship between treatment and outcome (the "dose-response curve"), which makes causal inference more challenging. This work proposes estimators using efficient influence functions (EIFs) for causal dose-response curves after propensity score trimming. Trimming involves estimating causal effects among subjects with propensity scores above a threshold, which addresses positivity violations that complicate estimation. Several challenges arise with continuous treatments. First, EIFs for trimmed dose-response curves do not exist, due to a lack of pathwise differentiability induced by trimming and a continuous treatment. Second, if the trimming threshold is not prespecified and is instead a parameter that must be estimated, then estimation uncertainty in the threshold must be accounted for. To address these challenges, we target a smoothed version of the trimmed dose-response curve for which an EIF exists. We allow the trimming threshold to be a user-specified quantile of the propensity score distribution, and we construct confidence intervals which reflect uncertainty involved in threshold estimation. Our resulting EIF-based estimators exhibit doubly-robust style guarantees, with error involving products or squares of errors for the outcome regression and propensity score. Thus, our estimators can exhibit parametric convergence rates even when the outcome regression and propensity score are estimated at slower nonparametric rates with flexible estimators. These findings are validated via simulation and an application, thereby showing how to efficiently-but-flexibly estimate a dose-response curve after trimming