Temporal blindspots in Occupy Philadelphia

ABSTRACT

This paper analyzes the disjunctive temporalities of Occupy Philadelphia’s political constituencies. Drawing on both an ethnographic participant observation study of the Occupy Philadelphia movement and Philadelphia’s neoanarchist political communities, and on recent social scientific theorization of events, the paper argues that contradictory ideas about temporal timescales, momentum, duration, sequences, and rhythms of tactical and strategic action problematized interaction and coordination among movement participants. These points of coordinative disjuncture can be traced back to differences in participants’ ideas about prefigurative politics and strategic temporalities. Limning the temporal expectations and experiences of social movement participants, this paper contributes to the examination of both linkages and disjunctures between eventful temporalities experienced in moments of protest and in social movements with diverse timescales.     

Modified quasi-profile likelihoods from estimating functions

We discuss higher-order adjustments for a quasi-profile likelihood for a scalar parameter of interest, in order to alleviate some of the problems inherent to the presence of nuisance parameters, such as bias and inconsistency. Indeed, quasi-profile score functions for the parameter of interest have bias of order O(1)$\mathrm{O}(1)$, and such bias can lead to poor inference on the parameter of interest. The higher-order adjustments are obtained so that the adjusted quasi-profile score estimating function is unbiased and its variance is the negative expected derivative matrix of the adjusted profile estimating equation. The modified quasi-profile likelihood is then obtained as the integral of the adjusted profile estimating function. We discuss two methods for the computation of the modified quasi-profile likelihoods: a bootstrap simulation method and a first-order asymptotic expression, which can be simplified under an orthogonality assumption. Examples in the context of generalized linear models and of robust inference are provided, showing that the use of a modified quasi-profile likelihood ratio statistic may lead to coverage probabilities more accurate than those pertaining to first-order Wald-type confidence intervals.     

Drivers of Youth Labour Market Integration Across European Regions

Territorial disparities and youth labour markets have been often considered as separated themes, due to challenges in data availability. Comparative regional or sub-regional research on youth labour market integration (YLMI) have been therefore scarce. In this article, we address this gap by presenting a composite measure of YLMI that covers a wide range of indicators and sheds light on the EU territorial divide of young peoples’ opportunities at regional level. In order to build the YLMI index, we use benefit-of-the-doubt-weighting, a seminal methodology on composite indicators (CI) that combines sequence with conditional weights based on the range of each sub-indicator. To proof the usefulness of YLMI, we analyze the evolution of regional YLMI in the EU before and after the economic crisis; and the trends of homogenization or differentiation across EU territories. Furthermore, we investigate to what extent employment conditions, skills supply and technological resources explain cross-regional variations in YLMI.

     

Extending conditional likelihood in models for stratified binary data

The conditional likelihood is widely used in logistic regression models with stratified binary data. In particular, it leads to accurate inference for the parameters of interest, which are common to all strata, eliminating stratum-specific nuisance parameters. The modified profile likelihood is an accurate approximation to the conditional likelihood, but has the advantage of being available for general parametric models. Here, we propose the modified profile likelihood as an ideal extension of the conditional likelihood in generalized linear models for binary data, with generic link function. An important feature is that for the implementation we only need standard outputs of routines for generalized linear models. The accuracy of the method is supported by theoretical properties and is confirmed by simulation results.This research was supported by MIUR COFIN 2001-2003.     

A computer algebra package for approximate conditional inference

This paper presents a set of REDUCE procedures that make a number of existing higher-order asymptotic results available for both theoretical and practical research. Attention has been restricted to the context of exact and approximate inference for a parameter of interest conditionally either on an ancillary statistic or on a statistic partially sufficient for the nuisance parameter. In particular, the procedures apply to regression-scale models and multiparameter exponential families. Most of them support algebraic computation as well as numerical calculation for a given data set. Examples illustrate the code.     

Restricted likelihood inference for generalized linear mixed models

We aim to promote the use of the modified profile likelihood function for estimating the variance parameters of a GLMM in analogy to the REML criterion for linear mixed models. Our approach is based on both quasi-Monte Carlo integration and numerical quadrature, obtaining in either case simulation-free inferential results. We will illustrate our idea by applying it to regression models with binary responses or count data and independent clusters, covering also the case of two-part models. Two real data examples and three simulation studies support the use of the proposed solution as a natural extension of REML for GLMMs. An R package implementing the methodology is available online.     

Linking global value chains and supply chain management: evidence from the electric motors industry

The global value chain (GVC) framework and its central concept of governance are increasingly advocated as powerful tools for interpreting managerial issues with particular reference to global supply chain (SC) management. However, a gap still exists about how the GVC concepts, which have been developed at the industry level, can be applied at the company level. The aim of this work is therefore to investigate how the concepts of GVC structure and governance are related to the way the SC is managed. Several research propositions drawn from the literature are investigated by means of seven case studies in the electric motors industry. The results show that the GVC can be a useful framework for understanding and deploying SC management at the company level. Moreover, the analysis of the governance modes provides an effective tool to explain the existing degree of technological and operational collaboration in the SC. Finally, we show the importance of considering such contextual factors as company size and the competitive priorities of the company to move seamlessly between the GVC, at the industry level, and SC management, at the company level.     

Integrated Likelihood Inference in Small Sample Meta‐analysis for Continuous Outcomes

This paper proposes the use of the integrated likelihood for inference on the mean effect in small‐sample meta‐analysis for continuous outcomes. The method eliminates the nuisance parameters given by variance components through integration with respect to a suitable weight function, with no need to estimate them. The integrated likelihood approach takes into proper account the estimation uncertainty of within‐study variances, thus providing confidence intervals with empirical coverage closer to nominal levels than standard likelihood methods. The improvement is remarkable when either (i) the number of studies is small to moderate or (ii) the small sample size of the studies does not allow to consider the within‐study variances as known, as common in applications. Moreover, the use of the integrated likelihood avoids numerical pitfalls related to the estimation of variance components which can affect alternative likelihood approaches. The proposed methodology is illustrated via simulation and applied to a meta‐analysis study in nutritional science.     

Structural funds and sustainable development the SQM approach

The question of how to achieve greater levels of sustainable development is intrinsically linked with the discussion concerning new forms of governance. Structural funds have become most influential in promoting sustainable development and appropriate forms of governance across the EU. They have been very important in introducing new innovative forms of co‐ordination in many countries and have encouraged the mobilization of new political actors. Structural Funds can be considered as a most interesting laboratory for the development of new governance patterns, which are urgently needed for coping with accelerated change and increasing complexity. Multi‐level governance in the spirit of subsidiarity will not be possible without flexible objective‐oriented management approaches instead of the rigid attribution of competences. This requires new conceptual approaches, procedures, and instruments. ‘SQM—Sustainable Quality Management®’ is a coherent system for the conception, support, monitoring and evaluation of sustainable development processes. A series of pilot projects in the last five years have shown its potential and utility. The SQM system includes concepts, methods and operational tools that have proved to be applicable and comprehensible in different European cultures. Internet‐based SQM software tools support every step in the policy cycle. Sustainable development is conceived as an overarching principle that governs the management of processes and covers all policy principles postulated by the EU. In the use of a common framework over the whole policy cycle and the coherent implementation of basic principles there is the promise of achieving better orientation towards sustainable development and considerable efficiency gains.