Challenging reductionism in analyses of EU-Russia energy relations

No abstract available

A Vicious Cycle: How Racialised Moral Panics Simultaneously Reproduce (and are Reproduced by) Repressive Policing Practices

Policing and moral panics exist in a mutually reinforcing, reciprocal relationship, the harmful outcomes of which are disproportionately directed towards poor communities of colour. This paper will draw on two examples of moral panics: those surrounding Islamic terrorism and Black crime, in order to illustrate the harm that this reinforcing relationship can cause. This harm manifests itself in increasingly restrictive antiterrorism laws, Prevent initiatives, racial profiling, and internal surveillance within the Muslim community; as well as the policies of Joint Enterprise, Knife Crime Prevention Orders (KCPOs), and the strengthening of the school-to-prison pipeline, which disproportionally target Black youth. With reference to Hall et al’s notion of a ‘law and order society’, this paper will argue that these moral panics, rather than being wholly distinct, rather, bleed into one another. Whilst they target their own ’folk devils’ and manifest independently through policies that target specific ethnic or religious groups, they cumulatively serve to justify increasingly repressive policing practices. It is the control of perceived racial, cultural, or religious ‘others’, or deviants, that these moral panics serve to justify. This network of interconnected moral panics is self-perpetuating; policing acts as a catalyst for these panics and, at the same time, is presented as the solution to them

PART-FARM GENERAL CROPLAND RETIREMENT: EFFECTS OF SOME ALTERNATIVE PROGRAM SPECIFICATIONS

Land Economics/Use,

Bayesian regression discontinuity designs: Incorporating clinical knowledge in the causal analysis of primary care data

The regression discontinuity (RD) design is a quasi-experimental design that estimates the causal effects of a treatment by exploiting naturally occurring treatment rules. It can be applied in any context where a particular treatment or intervention is administered according to a pre-specified rule linked to a continuous variable. Such thresholds are common in primary care drug prescription where the RD design can be used to estimate the causal effect of medication in the general population. Such results can then be contrasted to those obtained from randomised controlled trials (RCTs) and inform prescription policy and guidelines based on a more realistic and less expensive context. In this paper we focus on statins, a class of cholesterol-lowering drugs, however, the methodology can be applied to many other drugs provided these are prescribed in accordance to pre-determined guidelines. NHS guidelines state that statins should be prescribed to patients with 10 year cardiovascular disease risk scores in excess of 20%. If we consider patients whose scores are close to this threshold we find that there is an element of random variation in both the risk score itself and its measurement. We can thus consider the threshold a randomising device assigning the prescription to units just above the threshold and withholds it from those just below. Thus we are effectively replicating the conditions of an RCT in the area around the threshold, removing or at least mitigating confounding. We frame the RD design in the language of conditional independence which clarifies the assumptions necessary to apply it to data, and which makes the links with instrumental variables clear. We also have context specific knowledge about the expected sizes of the effects of statin prescription and are thus able to incorporate this into Bayesian models by formulating informative priors on our causal parameters.Comment: 21 pages, 5 figures, 2 table

Survival extrapolation using the poly-Weibull model.

Recent studies of (cost-) effectiveness in cardiothoracic transplantation have required estimation of mean survival over the lifetime of the recipients. In order to calculate mean survival, the complete survivor curve is required but is often not fully observed, so that survival extrapolation is necessary. After transplantation, the hazard function is bathtub-shaped, reflecting latent competing risks which operate additively in overlapping time periods. The poly-Weibull distribution is a flexible parametric model that may be used to extrapolate survival and has a natural competing risks interpretation. In addition, treatment effects and subgroups can be modelled separately for each component of risk. We describe the model and develop inference procedures using freely available software. The methods are applied to two problems from cardiothoracic transplantation

Enabling knowledge brokerage intermediaries to be evidence-informed

TARGET AUDIENCE: What Works Centres; other intermediary brokerage agencies; their funders and users; and researchers of research use. BACKGROUND: Knowledge brokerage and knowledge mobilisation (KM) are generic terms used to describe activities to enable the use of research evidence to inform policy, practice and individual decision making. Knowledge brokerage intermediary (KBI) initiatives facilitate such use of research evidence. This debate paper argues that although the work of KBIs is to enable evidence-informed decision making (EIDM), they may not always be overt and consistent in how they follow the principles of EIDM in their own practice. KEY POINTS FOR DISCUSSION: Drawing on examples from existing brokerage initiatives, four areas are suggested where KBIs could be more evidence-informed in their work: (1) needs analysis: evidence-informed in their analysis of where and how the KBI can best contribute to the existing evidence ecosystem; (2) methods and theories of change: evidence-informed in the methods that the KBI uses to achieve its goals; (3) evidence standards: credible standards for making evidence claims; and (4) evaluation and monitoring: evidence-informed evaluation of their own activities and contribution to the knowledge base on evidence use. For each of these areas, questions are suggested for considering the extent that the principles are being followed in practice. CONCLUSIONS AND IMPLICATIONS: KBIs work with evidence but they may not always be evidence-informed in their practice. KBIs could benefit from more overtly attending to the extent that they apply the logic of EIDM to how they work. In doing so, KBIs can advance both the study, and practice, of using research evidence to inform decision making

Russian approaches to energy security and climate change: Russian gas exports to the EU

The proposition that EU climate policy represents a threat to Russia’s gas exports to the EU, and therefore to Russia’s energy security, is critically examined. It is concluded that whilst the greater significance of climate-change action for Russian energy security currently lies not in Russia’s own emissions reduction commitments but in those of the EU, an even greater threat to Russia’s energy security is posed by the development of the EU internal gas market and challenges to Russia’s participation in that market. However, the coming decades could see Russia’s energy security increasingly influenced by climate-change action policies undertaken by current importers of Russian gas such as the EU, and potential importers such as China and India. The challenge for Russia will be to adapt to developments in energy security and climate-change action at the European and global levels

Survival extrapolation in the presence of cause specific hazards.

Health economic evaluations require estimates of expected survival from patients receiving different interventions, often over a lifetime. However, data on the patients of interest are typically only available for a much shorter follow-up time, from randomised trials or cohorts. Previous work showed how to use general population mortality to improve extrapolations of the short-term data, assuming a constant additive or multiplicative effect on the hazards for all-cause mortality for study patients relative to the general population. A more plausible assumption may be a constant effect on the hazard for the specific cause of death targeted by the treatments. To address this problem, we use independent parametric survival models for cause-specific mortality among the general population. Because causes of death are unobserved for the patients of interest, a polyhazard model is used to express their all-cause mortality as a sum of latent cause-specific hazards. Assuming proportional cause-specific hazards between the general and study populations then allows us to extrapolate mortality of the patients of interest to the long term. A Bayesian framework is used to jointly model all sources of data. By simulation, we show that ignoring cause-specific hazards leads to biased estimates of mean survival when the proportion of deaths due to the cause of interest changes through time. The methods are applied to an evaluation of implantable cardioverter defibrillators for the prevention of sudden cardiac death among patients with cardiac arrhythmia. After accounting for cause-specific mortality, substantial differences are seen in estimates of life years gained from implantable cardioverter defibrillators

Inter and intra-rater reliability of head posture assessment through observation

The purpose of this study is to assess inter and intra-rater reliability of head posture (HP) assessment through observation