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like “justice,”“peace” and “democracy” that could be interpreted morally by the masses, while party leaders and intellectuals upheld a historically materialist vision in which those same words were essentially meaningless (in fact, Marx himself had already mocked them as “Romantic Socialism”...
30) Here, in the context of self-referential processing, we hypothesize that the integration of wakeful CAT and sleep-based TMR could change how individuals perceive and endorse positive personality traits as self-descriptive. Specifically, while CAT would increase salience of specific positive traits...
As we interact with more Deaf communities, we continually learn about new apps that Deaf people use to communicate. In other words, ICT literacy is 'catchy', and spreads, thus paving the way for positive deviance to spread. ICT amplification is clearly enabled by SignSupport, a mobile app ...
room being talked at or PowerPointed to death. What I remember vividly from a long-ago Scrum training is not the words of wisdom falling from the instructor’s lips, but rather the games, exercises, and conversations with other participants that illustrated and reinforced the ideas being ...
Negative states and Miscellaneous (for words that cannot be clearly associated to positive or negative states). Excluding “peace”, “beauteous” and “tranquility”, which already had their categories, all the other words were classified as belonging to one of the five mentioned categories, by ...
The findings indicate that a taboo exists with regards to the discussion of positive action processes in the police workplace. A juxtaposition also exists between the existence of positive action initiatives and the theme of meritocracy amongst the police officers. Officers strongly refuted the need ...
In the current climate of Covid-19 and world-wide social distancing, the mental health toll has been widely reported, with an expectation that the negative
Most of what companies know about their customers tends to be descriptive and data driven: who they are, where they live, what they’ve purchased, how long they’ve been a customer, etc… There may be a segmentation analysis that groups customers by attitudes, etc… However, in most cases...