A study of the determinants of environmental disclosure quality: evidence from French listed companies

Journal of Management and Governance - We examine the impact of various factors on the quality of environmental disclosure. Combining multi-theories in a unique framework, it focuses on factors...     

What’s the Confusion About Fusion?—Differentiating Positive and Negative Closeness in Lesbian Relationships

This study differentiated between closeness and fusion in lesbian relationships, and examined whether age, adult attachment style, social support, outness, and relationship satisfaction were associated with these variables. Participants consisted of 77 women in long-term, lesbian relationships. Overall, women who reported showing greater closeness toward their partners were more satisfied in their relationships. Age and attachment style were better predictors of closeness and fusion than were social support and outness. The theoretical implications of these findings are discussed. Findings highlight the need for therapists to distinguish between positive and negative types of closeness in lesbian relationships, and avoid pathologizing high levels of closeness in lesbian relationships simply because they may deviate from a heterosexual norm.     

Book Review: Learning NGOs and the Dynamics of Development Partnership,by Farhad Hossain,Marko Ulvila,and Ware Newaz (eds.). Dhaka Ahsania Mission,Dhaka, Bangladesh, 2000

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations -     

Testing Inference from Logistic Regression Models in Data with Unobserved Heterogeneity at Cluster Levels

Clustering due to unobserved heterogeneity may seriously impact on inference from binary regression models. We examined the performance of the logistic, and the logistic-normal models for data with such clustering. The total variance of unobserved heterogeneity rather than the level of clustering determines the size of bias of the maximum likelihood (ML) estimator, for the logistic model. Incorrect specification of clustering as level 2, using the logistic-normal model, provides biased estimates of the structural and random parameters, while specifying level 1, provides unbiased estimates for the former, and adequately estimates the latter. The proposed procedure appeals to many research areas.     

Feature combinations and the bhattacharyya criterion

We develop a procedure for calculating a kxn rank k matrix B for data compression using the Bhattacharyya bound on the probability of error and an iterative construction using Householder transformations. Two sets of remotely sensed agricultural data are used to demonstrate the application of the procedure. The results of the applications give some indication of the extent to which the Bhattacharyya bound on the probability of error is affected by such transformations for multivariate normal populations.     

Iraqi IDPs Access to Durable Solutions: Results of Two Rounds of a Longitudinal Study

This article discusses the findings from a 4,000 household, longitudinal study conducted by the International Organization for Migration (IOM) and Georgetown University. Using the Inter‐Agency Standing Committee (IASC) Framework on Durable Solutions, we investigate the circumstances in which households were displaced, and how their needs, strategies, and access to durable solutions change over time as they integrate, return, or settle elsewhere. Findings from the study thus allow us to build an evidence base that helps researchers and policymakers to move beyond conceptions of displacement as either a ‘crisis’ or a problem that has been solved, and instead bring into focus the ways in which displaced people find ways to rebuild their lives and livelihoods that coexist alongside patterns of mobility and risk management.     

A multi-scalar critical analysis of return migration policies in Mexico

Services and resources for migrants returning to Mexico are necessary to ease their transition and “re-integration” into home communities. Policies that do not have a holistic approach can result in serious implications for the social, political, cultural, and health of returnees, receiving families, and communities. This research critically analyses return migration policies in Mexico drawing from the intersectionality-based policy analysis framework and a multi-scalar approach to critically study return migration policies in Mexico. We analysed 20 return migration policies using the principles of the intersectionality-based policy analysis framework. In 2021, we interviewed those impacted by return migration policies in Veracruz, Mexico to gain deeper insights into return migration policies. Women who stayed behind, return migrants, community leaders, and health-care providers were interviewed via phone or face-to-face in Spanish. Information was transcribed verbatim and analysed with the aid of computer-assisted data analysis software and quotes were translated into English. They shed light on two major inequities in policies: (1) the lack of acknowledgement of diversity or return migrants and (2) the exclusion of receiving families and communities from the “re-integration” process of return migrants. Based on the multi-scalar critical policy analysis, return migration policies in Mexico would benefit from a more comprehensive and inclusive approach where the needs of return migrants and community members are protected based on their diversity.