Women’s entrenched workforce participation has contributed to the rise in dual-earner households over the last two decades in Germany. Also, it contributes empirical evidence to the connection between individual or travel characteristics and access to green street landscape of men and women. This study tested and reported the disparities in green exposure of residents with different genders. (3) Individual and travel characteristics result in different green exposure, and different travel modes may enhance or weaken men and women’s exposure to green spaces in different ways. Thus, they experience higher levels of green exposure of unit travel distance. (2) Women are more likely to choose green, pleasant, and safe travel routes than men. The results provided three main insights: (1) Men enjoyed greater overall green exposure than women because they are generally less restricted when traveling. We used 7,880 GPS trip tracking data from 662 respondents in Haidian District, Beijing, and combined these with street view big data and machine learning to calculate the green view index for constructing a novel method of measuring green exposure. In this context, the present research attempted to develop and explore a broad analytical theme, namely, examine whether green exposure between genders is equal. In addition, many studies discussed gender as a variable rather than the main focus.
The majority of literature used residential areas as the analysis unit to evaluate green space, which may lead to biased estimates because it ignores daily mobility. However, the exposure of different social groups to urban greenness is not always equal. Good urban green space is conducive to the physical and mental health of residents. For both the groups, men or women with more egalitarian or reverse working hours preferences are more likely to use sustainable modes. For respondents with young children, increase in personal income positively and significantly predicts women's (also men's) driving, whereas high levels of education, increase in household income and partners’ time spent on unpaid work strongly decrease women’s driving. For respondents without young children, the spatial and temporal fixity attributes strongly predict men’s (also women's) driving, whereas for working in market/non-market sectors, partner attributes significantly decrease men’s driving. In general, our results suggest that the direction of coefficients is more similar than different for both men and women. We use the German National Time Use Survey 2012/13 and adopt multinomial logit analysis. We explore the associations between work-trip mode choice and five key elements: i) personal socio-economic status ii) household attributes, iii) spatio-temporal fixity, iv) partner interaction and v) working hours preferences. In doing so, we develop four separate models for women and men with and without children, respectively. In this regard, the purpose of the study is to determine if individuals’ commuting mode decisions vary with gender and the presence of young children.
Free version similar to tripmode free#
(The kind of app I was looking for was TripMode as suggested by u/cortex13b, albeit a free version ).
Free version similar to tripmode mac#
Then there's Radio Silence that may well fit your needs. The app Hands Off! Appears to be no longer developed (site offline). The aforementioned Lulu has a good reputation. Little Snitch vs TripMode 3 - monitoring my web traffic Little Snitch (LS) is considered by many to be the gold standard.I’ve made an App to monitor and control your internet usage How is this different from TripMode ()? The main UI is even identical.Mac Power Users 653: Workflows with Chris Christensen More Power Users: Ad-free episodes with regular bonus segmentsChris Christensen / TwitterMomenta Pentop Computer's Design and TechnologyRemembering eWorld, Apple's forgotten online service | Macworld30-plus years of HyperCard, the missing link to the Web | Ars TechnicaHow The Newton And ARM Saved Apple From Death | The CPU Shack MuseumThree Tiny Laptops - MacStoriesDowncast AppForecast: Podcast MP3.
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