The Experts below are selected from a list of 75693 Experts worldwide ranked by ideXlab platform

Charis E Kubrin - One of the best experts on this subject based on the ideXlab platform.

  • structural factors and black interracial homicide a new examination of the Causal Process
    Criminology, 2004
    Co-Authors: Tim Wadsworth, Charis E Kubrin
    Abstract:

    This study evaluates the assumption that deprivation among African Americans and racial inequality lead to black interracial homicide due to racial conflict and antagonism. Using refined race-adjusted Supplemental Homicide Report data, Uniform Crime Report data and census data, we test an alternative hypothesis that draws on the macrostructural opportunity theory to assess and more accurately specify the relationship between structural characteristics and black interracial homicide. We find that first, the relationship between economic factors and black interracial homicide can be explained in large part by high rates of financially motivated crime such as robbery, and second, that economic factors are associated with financially motivated but not expressive black interracial killings. Analyses of black intraracial killings are performed for comparison purposes. Collectively, the findings suggest that conflict-based explanations rooted in racial antagonism and frustration aggression may be premature.

  • structural factors and black interracial homicide a new examination of the Causal Process
    Social Science Research Network, 2004
    Co-Authors: Tim Wadsworth, Charis E Kubrin
    Abstract:

    This study evaluates the assumption that deprivation among African Americans and racial inequality lead to black interracial homicide due to racial conflict and antagonism. Using refined race-adjusted Supplemental Homicide Report data, Uniform Crime Report data, and Census data, we test an alternative hypothesis that draws on the macrostructural opportunity theory and the routine activities perspective to assess, and more accurately specify, the relationship between structural characteristics and black interracial homicide. The study finds that first, the relationship between economic factors and black interracial homicide can be explained, in large part, by high rates of financially-motivated crime such as robbery, and second, that economic factors are associated with financially-motivated but not expressive black interracial killings. Analyses of black intraracial killings are also performed for comparison purposes. Collectively, the findings suggest that conflict-based explanations that are rooted in racial antagonism and frustration aggression may be premature.

Josep A Rossello - One of the best experts on this subject based on the ideXlab platform.

  • can extensive reticulation and concerted evolution result in a cladistically structured molecular data set
    Cladistics, 2001
    Co-Authors: Gonzalo Nieto Feliner, Javier Fuertes Aguilar, Josep A Rossello
    Abstract:

    Hierarchy is the main criterion for informativeness in a data set, even if no explicit reference to evolution as a Causal Process is provided. Sequence data (nuclear ribosomal DNA ITS) from Armeria (Plumbaginaceae) contains a certain amount of hierarchical structure as suggested by data decisiveness and distribution of tree lengths. However, ancillary evidence suggests that extensive gene flow and biased concerted evolution in these multicopy regions have significantly shaped the ITS data set. This argument is discussed using parsimony analysis of four data sets, constructed by combining wild sequences with those from different generations of artificial hybrids (wild + F1, F2, and backcrosses; wild + backcrosses; wild + F1; wild + F2). Compared to the F1 hybrids, F2 show a certain degree of homogenization in polymorphic sites. This effect reduces topological disruption caused by F1 and is considered to be illustrative of how extensive gene flow and biased concerted evolution may have modeled the wild ITS data. The possibility that hierarchy has arisen as a result of—or despite a significant contribution from—those two such potentially perturbing forces raises the question of what kind of signal are we recovering from this molecular data set.

  • regular articlecan extensive reticulation and concerted evolution result in a cladistically structured molecular data set
    Cladistics, 2001
    Co-Authors: Gonzalo Nieto Feliner, Javier Fuertes Aguilar, Josep A Rossello
    Abstract:

    Hierarchy is the main criterion for informativeness in a data set, even if no explicit reference to evolution as a Causal Process is provided. Sequence data (nuclear ribosomal DNA ITS) from Armeria (Plumbaginaceae) contains a certain amount of hierarchical structure as suggested by data decisiveness and distribution of tree lengths. However, ancillary evidence suggests that extensive gene flow and biased concerted evolution in these multicopy regions have significantly shaped the ITS data set. This argument is discussed using parsimony analysis of four data sets, constructed by combining wild sequences with those from different generations of artificial hybrids (wild + F1, F2, and backcrosses; wild + backcrosses; wild + F1; wild + F2). Compared to the F1 hybrids, F2 show a certain degree of homogenization in polymorphic sites. This effect reduces topological disruption caused by F1 and is considered to be illustrative of how extensive gene flow and biased concerted evolution may have modeled the wild ITS data. The possibility that hierarchy has arisen as a result of—or despite a significant contribution from—those two such potentially perturbing forces raises the question of what kind of signal are we recovering from this molecular data set.

Tim Wadsworth - One of the best experts on this subject based on the ideXlab platform.

  • structural factors and black interracial homicide a new examination of the Causal Process
    Criminology, 2004
    Co-Authors: Tim Wadsworth, Charis E Kubrin
    Abstract:

    This study evaluates the assumption that deprivation among African Americans and racial inequality lead to black interracial homicide due to racial conflict and antagonism. Using refined race-adjusted Supplemental Homicide Report data, Uniform Crime Report data and census data, we test an alternative hypothesis that draws on the macrostructural opportunity theory to assess and more accurately specify the relationship between structural characteristics and black interracial homicide. We find that first, the relationship between economic factors and black interracial homicide can be explained in large part by high rates of financially motivated crime such as robbery, and second, that economic factors are associated with financially motivated but not expressive black interracial killings. Analyses of black intraracial killings are performed for comparison purposes. Collectively, the findings suggest that conflict-based explanations rooted in racial antagonism and frustration aggression may be premature.

  • structural factors and black interracial homicide a new examination of the Causal Process
    Social Science Research Network, 2004
    Co-Authors: Tim Wadsworth, Charis E Kubrin
    Abstract:

    This study evaluates the assumption that deprivation among African Americans and racial inequality lead to black interracial homicide due to racial conflict and antagonism. Using refined race-adjusted Supplemental Homicide Report data, Uniform Crime Report data, and Census data, we test an alternative hypothesis that draws on the macrostructural opportunity theory and the routine activities perspective to assess, and more accurately specify, the relationship between structural characteristics and black interracial homicide. The study finds that first, the relationship between economic factors and black interracial homicide can be explained, in large part, by high rates of financially-motivated crime such as robbery, and second, that economic factors are associated with financially-motivated but not expressive black interracial killings. Analyses of black intraracial killings are also performed for comparison purposes. Collectively, the findings suggest that conflict-based explanations that are rooted in racial antagonism and frustration aggression may be premature.

Markus Haverland - One of the best experts on this subject based on the ideXlab platform.

  • case studies and Causal Process tracing
    Social Science Research Network, 2014
    Co-Authors: Joachim Blatter, Markus Haverland
    Abstract:

    Case-study research has been defined by Yin as an in-depth investigation of (contemporary) phenomena in a real-life context, particularly equipped to answer how and why questions (2009: pp. 8–18). Yin and other authors of case studies offer various analytical strategies for studying one of a few cases in depth, ranging from theoretically informed pattern matching (Yin, 2009) to strongly inductive approaches (Stake, 1995). This chapter deals with one specific approach: Causal-Process Tracing (CPT). This methodological approach is particularly well suited to answer ‘why’ and ‘how’ questions because it focuses on the Causal conditions, configurations and mechanisms which make a specific outcome possible. It is outcome (Y)-centred, which means that the researcher is interested in the many and complex causes of a specific outcome and not so much in the effects of a specific cause (X). In other words, CPT is geared to answer questions like ‘why did this (Y) happen?’ Furthermore, its aim is to reveal the sequential and situational interplay between Causal conditions and mechanisms in order to show in detail how these Causal factors generate the outcome of interest.

  • Causal Process tracing
    Social Science Research Network, 2012
    Co-Authors: Joachim Blatter, Markus Haverland
    Abstract:

    In most small-N studies, the tracing of Causal Processes plays an important role. Very often, Causal-Process tracing (CPT) is used as a complementary technique to co-variational analysis (COV). Tracing the Process that leads from a Causal factor to an outcome makes it possible to enhance the internal validity of a Causal claim that ‘x matters’ (Gerring 2007a: 173–84). This ‘added value’ is especially warranted when the compared cases are not as similar as they should be (to be ‘controlled’), when the co-variatonal analysis is indeterminate (because more than one independent variable co-varies with the dependent variable in a theoretically meaningful way), or when the measurement and classification of variables is not as clear-cut as it should be. We will provide examples for the combination of COV and CPT in Section 5.2, wherein we address overlaps and combinations of the three approaches to case study research.

Joachim Blatter - One of the best experts on this subject based on the ideXlab platform.

  • case studies and Causal Process tracing
    Social Science Research Network, 2014
    Co-Authors: Joachim Blatter, Markus Haverland
    Abstract:

    Case-study research has been defined by Yin as an in-depth investigation of (contemporary) phenomena in a real-life context, particularly equipped to answer how and why questions (2009: pp. 8–18). Yin and other authors of case studies offer various analytical strategies for studying one of a few cases in depth, ranging from theoretically informed pattern matching (Yin, 2009) to strongly inductive approaches (Stake, 1995). This chapter deals with one specific approach: Causal-Process Tracing (CPT). This methodological approach is particularly well suited to answer ‘why’ and ‘how’ questions because it focuses on the Causal conditions, configurations and mechanisms which make a specific outcome possible. It is outcome (Y)-centred, which means that the researcher is interested in the many and complex causes of a specific outcome and not so much in the effects of a specific cause (X). In other words, CPT is geared to answer questions like ‘why did this (Y) happen?’ Furthermore, its aim is to reveal the sequential and situational interplay between Causal conditions and mechanisms in order to show in detail how these Causal factors generate the outcome of interest.

  • Causal Process tracing
    Social Science Research Network, 2012
    Co-Authors: Joachim Blatter, Markus Haverland
    Abstract:

    In most small-N studies, the tracing of Causal Processes plays an important role. Very often, Causal-Process tracing (CPT) is used as a complementary technique to co-variational analysis (COV). Tracing the Process that leads from a Causal factor to an outcome makes it possible to enhance the internal validity of a Causal claim that ‘x matters’ (Gerring 2007a: 173–84). This ‘added value’ is especially warranted when the compared cases are not as similar as they should be (to be ‘controlled’), when the co-variatonal analysis is indeterminate (because more than one independent variable co-varies with the dependent variable in a theoretically meaningful way), or when the measurement and classification of variables is not as clear-cut as it should be. We will provide examples for the combination of COV and CPT in Section 5.2, wherein we address overlaps and combinations of the three approaches to case study research.

  • co variation and Causal Process tracing revisited clarifying new directions for Causal inference and generalization in case study methodology
    2008
    Co-Authors: Joachim Blatter, Till Blume
    Abstract:

    ion Drawing conclusions from adequacy for the 1. Specification and justification of the range of empirical case(s) to the relavance/relative theories which are applied strength of theories within the broader 2. Selecting cases according to their “likeliness” scientific discourse for the dominant theory son within the case study proper ceases to play a substantial role within the co-variational template. This is due to the fact that the authors dismiss the most-different cases technique and that all other techniques are geared to select only one case. In consequence, Gerring and Seawright in fact challenge an assumption that has become (implicitly or explicitly) commonsensical, especially in comparative politics: the assumption that analyzing and comparing a few cases in-depth is better than analyzing one case. This leaves us with the following puzzle: If we want to generalize towards a population and if–given this goal–the cross-case comparison must include (a representative sample of) the entire population, how does this correspond to the position presented in the book that “spatial comparison” (comparison of patterns of co-variation among a few cases) is a major element of generating internal validity? The part on “spatial comparison” is the shortest section within Chapter 6 (pp. 165-6). Whether a matter of accident or not, we take the fact as support for our following conclusion. For us, the core message from Gerring’s book (and this corresponds to George and Bennett as well)2 is the insight that the comparison of a few (from two until about six) cases does not provide much leverage for drawing Causal inferences. Instead, the combination of a large-N-study and in-depth analysis within single cases, which are selected on the basis of this large-N-study, is much more productive. Accordingly, the strength of Gerring’s book lies less in providing helpful advice for doing case studies proper but more in his profound discussion on how to embed case studies in large-N-studies.3 Overall, we predict that Gerring’s book will be received by case study researchers with some skepticism. Conceptually, the co-variational style represents what Peter Hall (2006: 26) aptly described as “the statistical method writ small” and practically, it confines case studies to a secondary place: beyond theory development, case studies are only seen as conducive for gaining Causal inference in combination with, and after, large-N studies. The combination of large-N and small-N studies might well be a fruitful endeavor, although there are some first cautious voices (e.g., Rohlfing 2008). But there is the danger that we miss the real qualities of case studies and do not develop the adequate methodological advice if we conceive case study research only within the confines of covariational analysis. In comparison to Gerring’s book, Alexander George and Andrew Bennett’s Case Studies and Theory Development in the Social Sciences is much broader in its understanding of what case studies are, and it puts a strong emphasis on Causal Process tracing as the heart of the case study endeavor. The richness of the book in terms of conceptual breadth and philosophical depth comes with a price, though. First, the structure of the book is surprising: Advice on how to do case studies is given before basic foundations (scientific realism as epistemological base and the goal to generate policy-relevant theory) and techniques (controlled comparison, congruence method,