Criticism and Counter-Criticism of Public Management: Strategy Models

Critical control is very important in scientific management. This paper presents models of critical and counter-critical public-management strategies, focusing on the types of criticism and counter-criticism manifested in parliamentary political debates. The paper includes: (i) a normative model showing how rational criticism can be carried out; (ii) a normative model for oral critical intervention; and (iii) a general motivational strategy model for criticisms and counter-criticisms. The paper also presents an example taken from everyday life.criticism, counter-criticism, public management, public administration, public policies, innovation in communication, communicative innovation, debate.

The Right’s Reasons: Constitutional Conflict and the Spread of Woman-Protective Anti-Abortion Argument

The Lecture offers a provisional first account of the rise and spread of WPAA. It traces the development of gender-based antiabortion advocacy, examining the rise of post-abortion syndrome (PAS) claims in the Reagan years and the first struggles in the antiabortion movement about whether the right to life is properly justified on the ground of women’s welfare. My story then follows changes in the abortion-harms-women claim, as it is transformed from PAS—a therapeutic and mobilizing discourse initially employed to dissuade women from having abortions and to recruit women to the antiabortion cause—into WPAA, a political discourse forged in the heat of movement conflict that seeks to persuade audiences outside the movement’s ranks in political campaigns and constitutional law. I tell a story in which social movement mobilization, coalition, and conflict each play a role in the evolution and spread of this constitutional argument, in the process forging new and distinctly modern ways to talk about the right to life and the role morality of motherhood in the therapeutic, public health, and political rights idiom of late twentieth-century America

Ethics and/or aesthetics? reflections on cosmetic surgery for adolescents

Cosmetic surgery entails various ethical issues, even more so in cases involving adolescent patients. Cosmetic surgeons need to take into account how modern societies consider physical appearance an essential component of everyday life, as well as the vulnerability of youths and adolescents. For that reason, it is imperative to thoroughly assess the psychological and emotional states, in addition to the motivations, of minor patients. That goal can be achieved through the use of the DAS-59, (the Derriford Appearance Scale)1 , an effective and dependable tool devised to evaluate the psychological difficulties and distress experienced by people living with problems of appearance. Prior to undergoing cosmetic surgery procedures, adolescents should be required to go through adequate counseling, over multiple sessions and extended to their family members as well, on account of the complex issues inherent in evaluating the risk-benefit ratio and a prospective patient's decision-making capability. A concerted effort on the part of surgeons, psychiatrists or psychologists is key in determining the real motivations behind a minor's decision to opt for cosmetic surgery in the first place. Possible psychiatric conditions may in fact prevent a minor from making a free, informed decision. From an ethical standpoint, cosmetic surgery procedures should be geared to serve the best interest of the minor patient, who may experience distress over his or her body image, from a health and psychological balance perspective and improve his or her social, affective and working life. Besides, cosmetic surgery should not be overly invasive compared to its potential benefits. Those procedures aimed at achieving ″ideal beauty″ are not desirable and ought to be banned. By virtue of such criteria, the authors have set out to evaluate the ethical admissibility of some aesthetic treatments. Thus, doctors should not consent to any request coming from their patients, but rather, intervene only in presence of an objective physical flaw or deformity, e.g. protruding ears, which have a potential to negatively affect social life and interactions

#Brexit: Leave or Remain? The Role of User's Community and Diachronic Evolution on Stance Detection

[EN] Interest has grown around the classification of stance that users assume within online debates in recent years. Stance has been usually addressed by considering users posts in isolation, while social studies highlight that social communities may contribute to influence users¿ opinion. Furthermore, stance should be studied in a diachronic perspective, since it could help to shed light on users¿ opinion shift dynamics that can be recorded during the debate. We analyzed the political discussion in UK about the BREXIT referendum on Twitter, proposing a novel approach and annotation schema for stance detection, with the main aim of investigating the role of features related to social network community and diachronic stance evolution. Classification experiments show that such features provide very useful clues for detecting stance.The work of P. Rosso was partially funded by the Spanish MICINN under the research projects MISMIS-FAKEnHATE on Misinformation and Miscommunication in social media: FAKE news and HATE speech(PGC2018-096212-B-C31) and PROMETEO/2019/121 (DeepPattern) of the Generalitat Valenciana. The work of V. Patti and G. Ruffo was partially funded by Progetto di Ateneo/CSP 2016 Immigrants, Hate and Prejudice in Social Media (S1618 L2 BOSC 01).Lai, M.; Patti, V.; Ruffo, G.; Rosso, P. (2020). #Brexit: Leave or Remain? The Role of User's Community and Diachronic Evolution on Stance Detection. Journal of Intelligent & Fuzzy Systems. 39(2):2341-2352. https://doi.org/10.3233/JIFS-179895S23412352392Blondel, V. D., Guillaume, J.-L., Lambiotte, R., & Lefebvre, E. (2008). Fast unfolding of communities in large networks. Journal of Statistical Mechanics: Theory and Experiment, 2008(10), P10008. doi:10.1088/1742-5468/2008/10/p10008Deitrick, W., & Hu, W. (2013). Mutually Enhancing Community Detection and Sentiment Analysis on Twitter Networks. Journal of Data Analysis and Information Processing, 01(03), 19-29. doi:10.4236/jdaip.2013.13004Duranti A. and Goodwin C. , Rethinking context: Language as an interactive phenomenon, Cambridge University Press, (1992).Evans A. , Stance and identity in Twitter hashtags, Language@ Internet 13(1) (2016).Fortunato, S. (2010). Community detection in graphs. Physics Reports, 486(3-5), 75-174. doi:10.1016/j.physrep.2009.11.002Gelman, A., & King, G. (1993). Why Are American Presidential Election Campaign Polls So Variable When Votes Are So Predictable? British Journal of Political Science, 23(4), 409-451. doi:10.1017/s0007123400006682Gonçalves, B., Perra, N., & Vespignani, A. (2011). Modeling Users’ Activity on Twitter Networks: Validation of Dunbar’s Number. PLoS ONE, 6(8), e22656. doi:10.1371/journal.pone.0022656González, M. C., Hidalgo, C. A., & Barabási, A.-L. (2008). Understanding individual human mobility patterns. Nature, 453(7196), 779-782. doi:10.1038/nature06958Hernández-Castañeda, Á., Calvo, H., & Gambino, O. J. (2018). Impact of polarity in deception detection. Journal of Intelligent & Fuzzy Systems, 35(1), 549-558. doi:10.3233/jifs-169610Lazer, D., Pentland, A., Adamic, L., Aral, S., Barabási, A.-L., Brewer, D., … Van Alstyne, M. (2009). Computational Social Science. Science, 323(5915), 721-723. doi:10.1126/science.1167742Mohammad, S. M., Sobhani, P., & Kiritchenko, S. (2017). Stance and Sentiment in Tweets. ACM Transactions on Internet Technology, 17(3), 1-23. doi:10.1145/3003433Mohammad, S. M., & Turney, P. D. (2012). CROWDSOURCING A WORD-EMOTION ASSOCIATION LEXICON. Computational Intelligence, 29(3), 436-465. doi:10.1111/j.1467-8640.2012.00460.xPang, B., & Lee, L. (2008). Opinion Mining and Sentiment Analysis. Foundations and Trends® in Information Retrieval, 2(1–2), 1-135. doi:10.1561/1500000011Pennebaker J.W. , Francis M.E. and Booth R.J. , Linguistic Inquiry and Word Count: LIWC 2001, Mahway: Lawrence Erlbaum Associates 71 (2001).Sulis, E., Irazú Hernández Farías, D., Rosso, P., Patti, V., & Ruffo, G. (2016). Figurative messages and affect in Twitter: Differences between #irony, #sarcasm and #not. Knowledge-Based Systems, 108, 132-143. doi:10.1016/j.knosys.2016.05.035Theocharis, Y., & Lowe, W. (2015). Does Facebook increase political participation? Evidence from a field experiment. Information, Communication & Society, 19(10), 1465-1486. doi:10.1080/1369118x.2015.1119871Whissell, C. (2009). Using the Revised Dictionary of Affect in Language to Quantify the Emotional Undertones of Samples of Natural Language. Psychological Reports, 105(2), 509-521. doi:10.2466/pr0.105.2.509-52