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We present a two-assignment series that developed students' sociological imaginations and that could be done in a face-to-face or online course. The series used the Sociological Images blog and students' own visual images (e.g., photographs) to meet course learning goals: (1) link sociological theories and concepts to social events/trends, (2) apply these ideas to real life by identifying sociologically relevant images in daily life, and (3) communicate sociological analysis in academic and popular written forms. The use of a blog encourages students to embrace public sociology. We present faculty and student assessment data (pretest from nonequivalent comparisons group) from six lower division sociology classes at a regional university (N = 157). Students entered with little a priori ability to examine images using a sociological lens, and students who completed the series successfully applied sociological concepts and theories to critically examine elements of their lives, achieving core sociology disciplinary learning goals.

Active transportation modes such as walking and biking are gaining popularity for their extensive health and environmental benefits, yet scholars know little about how place-based accessibility varies by area sociodemographic composition. This study is among the first to examine sociodemographic disparities (by both race and socioeconomic status) in bikeability while allowing for heterogeneity in disparities. Consideration of bikeability disparities is particularly critical within the framework of urban planning concepts that promote equitable accessibility and reduced dependency on automobiles, such as the 15-minute city. Geographically Weighted Regressions examined associations between census tract-level bikeability (using an index that combines five components), socioeconomic status, and percentage non-White residents (controlling for age of structures in tracts). Findings showed that the strength and directionality of associations between bikeability and race/socioeconomic status varied throughout the county, providing targeted information on where greater concentrations of low socioeconomic status and non-White residents were associated with lower bikeability. [ABSTRACT FROM AUTHOR]