Response to the Letter to the Editor

This paper has attracted interest around the world from the media (both TV and newspapers). In addition, we have received letters, emails and telephone calls. One of our favorites was a voicemail message asking us to return a call to Australia at which point we would learn who really killed JFK. We welcome the opportunity to respond to the letter to the editor from Mr. Fiorentino. Mr. Fiorentino claims that our ``statement relating to the likelihood of a second assassin based on the premise of three or more separate bullets is demonstrably false.'' In response we would like to simply quote from page 327 of Gerald Posner's book Case Closed, one of the most well known works supporting the single assassin theory: ``If Connally was hit by another bullet, it had to be fired from a second shooter, since the Warren Commission's own reconstructions showed that Oswald could not have operated the bolt and refired in 1.4 seconds.'' Mr. Fiorentino also claims that the ``second fatal flaw is the use of a rather uncomplicated formula based on Bayes Theorem.'' Let $E$ denote the evidence and $T$ denote the theory that there were just two bullets (and hence a single shooter). We used Bayes Theorem to hypothetically calculate $P(T|E)$ from $P(E|T)$ and the prior probability $P(T)$. In order to make $P(T|E)$ ten times more likely than $P(\bar{T}|E)$, the ratio of the prior probabilities [i.e., $P(T) / P(\bar{T})$] would have to be greater than 15. Thus, we again conclude that this casts serious doubt on Dr. Guinn's conclusion that the evidence supported just two bullets. Sadly, this is far from the first time that probability has been misunderstood and/or misapplied in a case of public interest. A notable British example is the Clark case. See Nobles and Schiff (2005) for details. Finally, we welcome and, in fact, encourage members of the scientific community to provide alternative analyses of the data.Comment: Published in at http://dx.doi.org/10.1214/07-AOAS154 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Chemical and forensic analysis of JFK assassination bullet lots: Is a second shooter possible?

The assassination of President John Fitzgerald Kennedy (JFK) traumatized the nation. In this paper we show that evidence used to rule out a second assassin is fundamentally flawed. This paper discusses new compositional analyses of bullets reportedly to have been derived from the same batch as those used in the assassination. The new analyses show that the bullet fragments involved in the assassination are not nearly as rare as previously reported. In particular, the new test results are compared to key bullet composition testimony presented before the House Select Committee on Assassinations (HSCA). Matches of bullets within the same box of bullets are shown to be much more likely than indicated in the House Select Committee on Assassinations' testimony. Additionally, we show that one of the ten test bullets is considered a match to one or more assassination fragments. This finding means that the bullet fragments from the assassination that match could have come from three or more separate bullets. Finally, this paper presents a case for reanalyzing the assassination bullet fragments and conducting the necessary supporting scientific studies. These analyses will shed light on whether the five bullet fragments constitute three or more separate bullets. If the assassination fragments are derived from three or more separate bullets, then a second assassin is likely, as the additional bullet would not easily be attributable to the main suspect, Mr. Oswald, under widely accepted shooting scenarios [see Posner (1993), Case Closed, Bantam, New York].Comment: Published in at http://dx.doi.org/10.1214/07-AOAS119 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Hydrogeological controls on regional-scale indirect nitrous oxide (N2O) emission factors for rivers

Indirect nitrous oxide (N2O) emissions from rivers are currently derived using poorly constrained default IPCC emission factors (EF5r) which yield unreliable flux estimates. Here, we demonstrate how hydrogeological conditions can be used to develop more refined regional-scale EF5r estimates required for compiling accurate national greenhouse gas inventories. Focusing on three UK river catchments with contrasting bedrock and superficial geologies, N2O and nitrate (NO3-) concentrations were analyzed in 651 river water samples collected from 2011 to 2013. Unconfined Cretaceous Chalk bedrock regions yielded the highest median N2O-N concentration (3.0 μg L-1), EF5r (0.00036) and N2O-N flux (10.8 kg ha-1 a-1). Conversely, regions of bedrock confined by glacial deposits yielded significantly lower median N2O-N concentration (0.8 μg L-1), EF5r (0.00016) and N2O-N flux (2.6 kg ha-1 a-1), regardless of bedrock type. Bedrock permeability is an important control in regions where groundwater is unconfined, with a high N2O yield from high permeability Chalk contrasting with significantly lower median N2O-N concentration (0.7 μg L-1), EF5r (0.00020) and N2O-N flux (2.0 kg ha-1 a-1) on lower permeability unconfined Jurassic mudstone. The evidence presented here demonstrates EF5r can be differentiated by hydrogeological conditions and thus provide a valuable proxy for generating improved regional-scale N2O emission estimates

Navigating International, Interdisciplinary, and Indigenous Collaborative Inquiry

This report describes how multiple community constituents came together with university researchers to develop a shared agenda for studying young indigenous people in five international circumpolar communities. The paper focuses on the setup and process of an initial face-to-face methodological planning workshop involving youth and adult community members and academics. Members of Yup’ik, Inupiat, Eveny, Inuit, and Sámi communities from Siberia to Norway participated in the workshop and engaged in negotiations to arrive at shared research interests. This was essential since the ultimate goal of the research is translational and transformative, spurring social action in communities. Describing the beginning stage of this project and the underlying participatory methodology offers insight into how the approach engaged community members with varying degrees of sustained interest and practical success. It, therefore, articulates a methodological approach for international community-based participatory research

ConstitutionMaker: Interactively Critiquing Large Language Models by Converting Feedback into Principles

Large language model (LLM) prompting is a promising new approach for users to create and customize their own chatbots. However, current methods for steering a chatbot's outputs, such as prompt engineering and fine-tuning, do not support users in converting their natural feedback on the model's outputs to changes in the prompt or model. In this work, we explore how to enable users to interactively refine model outputs through their feedback, by helping them convert their feedback into a set of principles (i.e. a constitution) that dictate the model's behavior. From a formative study, we (1) found that users needed support converting their feedback into principles for the chatbot and (2) classified the different principle types desired by users. Inspired by these findings, we developed ConstitutionMaker, an interactive tool for converting user feedback into principles, to steer LLM-based chatbots. With ConstitutionMaker, users can provide either positive or negative feedback in natural language, select auto-generated feedback, or rewrite the chatbot's response; each mode of feedback automatically generates a principle that is inserted into the chatbot's prompt. In a user study with 14 participants, we compare ConstitutionMaker to an ablated version, where users write their own principles. With ConstitutionMaker, participants felt that their principles could better guide the chatbot, that they could more easily convert their feedback into principles, and that they could write principles more efficiently, with less mental demand. ConstitutionMaker helped users identify ways to improve the chatbot, formulate their intuitive responses to the model into feedback, and convert this feedback into specific and clear principles. Together, these findings inform future tools that support the interactive critiquing of LLM outputs