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  1. Decolonization Not Inclusion: Indigenous Resistance to American Settler Colonialism

    American Indians experience forms of domination and resist them through a wide range of decolonizing processes that are commonly overlooked, misidentified, or minimally analyzed by American sociology. This inattention reflects the naturalizing use of minoritizing frameworks regarding tribal members and ethnic rather than political conceptions of American Indian nationhood, membership, and identity.

  2. Critique of Glenn on Settler Colonialism and Bonilla-Silva on Critical Race Analysis from Indigenous Perspectives

    I critique Glenn’s article on settler colonialism and Bonilla-Silva’s article on critical race analysis from Indigenous perspectives, including racial genocide and world-systems analysis, to cover five centuries of global systemic racism during the conquest of the Americas, by Spanish and English colonizers and United States imperialism. I also propose macro-structural, comparative-historical analysis of racism including the destruction, resistance, and revitalization of Native Nations and American Indians.

  3. A “Real” American Indian

    Kimberly R. Huyser considers the power of stereotypes and self-image as she participates in a project to create modern images of Native Americans.
  4. How Environmental Decline Restructures Indigenous Gender Practices: What Happens to Karuk Masculinity When There Are No Fish?

    On the Klamath River in northern California, Karuk tribal fishermen traditionally provide salmon for food and ceremonies, yet the region has sustained serious environmental degradation in recent years. What happens to Karuk masculinity when there are no fish? Using interviews and public testimony, the authors examine how declining salmon runs affect the gender identities and practices of Karuk fishermen. Gendered practices associated with fishing serve ecological functions, perpetuate culture in the face of structural genocide, and unite families and communities.
  5. Nonlinear Autoregressive Latent Trajectory Models

    Autoregressive latent trajectory (ALT) models combine features of latent growth curve models and autoregressive models into a single modeling framework. The development of ALT models has focused primarily on models with linear growth components, but some social processes follow nonlinear trajectories. Although it is straightforward to extend ALT models to allow for some forms of nonlinear trajectories, the identification status of such models, approaches to comparing them with alternative models, and the interpretation of parameters have not been systematically assessed.
  6. Comment: Bayes, Model Uncertainty, and Learning from Data

    The problem of model uncertainty is a fundamental applied challenge in quantitative sociology. The authors’ language of false positives is reminiscent of Bonferroni adjustments and the frequentist analysis of multiple independent comparisons, but the distinct problem of model uncertainty has been fully formalized from a Bayesian perspective.
  7. We Ran 9 Billion Regressions: Eliminating False Positives through Computational Model Robustness

    False positive findings are a growing problem in many research literatures. We argue that excessive false positives often stem from model uncertainty. There are many plausible ways of specifying a regression model, but researchers typically report only a few preferred estimates. This raises the concern that such research reveals only a small fraction of the possible results and may easily lead to nonrobust, false positive conclusions. It is often unclear how much the results are driven by model specification and how much the results would change if a different plausible model were used.
  8. Comparing Regression Coefficients Between Same-sample Nested Models Using Logit and Probit: A New Method

    Logit and probit models are widely used in empirical sociological research. However, the common practice of comparing the coefficients of a given variable across differently specified models fitted to the same sample does not warrant the same interpretation in logits and probits as in linear regression. Unlike linear models, the change in the coefficient of the variable of interest cannot be straightforwardly attributed to the inclusion of confounding variables. The reason for this is that the variance of the underlying latent variable is not identified and will differ between models.

  9. Text Analysis with JSTOR Archives

    I provide a visual representation of keyword trends and authorship for two flagship sociology journals using data from JSTOR’s Data for Research repository. While text data have accompanied the digital spread of information, it remains inaccessible to researchers unfamiliar with the required preprocessing. The visualization and accompanying code encourage widespread use of this source of data in the social sciences.

  10. Reservation Lands as a Protective Social Factor: An Analysis of Psychological Distress among Two American Indian Tribes

    The unique physical, cultural, and ecological location of U.S. American Indian reservations simultaneously presents risks for mental health and offers sources of resilience to Native peoples. Using survey data from two American Indian tribes, we explore whether the length of one’s life spent on a reservation is associated with lower odds of psychological distress. In both tribes, we find that individuals who live a vast majority of their lives on the reservation have lower odds of psychological distress than individuals who spent portions of their life off or near the reservation.