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Статті в журналах з теми "Microinteractions"

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Автор: Grafiati

Опубліковано: 23 червня 2021

Оновлено: 26 квітня 2022

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1

Derné, Steve. "Hindu Men Talk about Controlling Women: Cultural Ideas as a Tool of the Powerful." Sociological Perspectives 37, no. 2 (June 1994): 203–27. http://dx.doi.org/10.2307/1389320.

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Hindu women's restrictions to the home and limited interactions with their husbands disadvantage Hindu women. These macro gender structures are constituted through microinteraction rituals. The article examines Hindu men's and women's microinteractions as a way of understanding Indian gender structure. Hindu men recognize their self-interest in these interaction rituals—they know that they benefit from women's subordination. Women's strategies of pursuing power and security in their husbands' families, moreover, often lead women into “bargains with patriarcy” that also contribute to the reconstitution of gender inequality in India.

2

Proaps, Alexandra. "Book Review: Microinteractions: Designing With Details." Ergonomics in Design: The Quarterly of Human Factors Applications 23, no. 4 (October 2015): 30–31. http://dx.doi.org/10.1177/1064804615613314b.

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3

Chen, X., R. Luo, W. W. Yuen, and T. G. Theofanous. "Experimental simulation of microinteractions in large scale explosions." Nuclear Engineering and Design 189, no. 1-3 (May 1999): 163–78. http://dx.doi.org/10.1016/s0029-5493(99)00032-1.

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4

Gudemenko, Dmitriy V., Vladimir I. Melikhov, and Oleg I. Melikhov. "Studying the Thermal Detonation Process Using the Microinteractions Model." Vestnik MEI, no. 2 (2017): 32–39. http://dx.doi.org/10.24160/1993-6982-2017-2-32-39.

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5

McDaniel, Rudy. "Understanding microinteractions as applied research opportunities for information designers." Communication Design Quarterly 3, no. 2 (March 27, 2015): 55–62. http://dx.doi.org/10.1145/2752853.2752860.

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6

Chen, X., W. W. Yuen, and T. G. Theofanous. "On the constitutive description of the microinteractions concept in steam explosions." Nuclear Engineering and Design 177, no. 1-3 (December 1997): 303–19. http://dx.doi.org/10.1016/s0029-5493(97)00138-6.

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7

Yuen, W. W., X. Chen, and T. G. Theofanous. "On the fundamental microinteractions that support the propagation of steam explosions." Nuclear Engineering and Design 146, no. 1-3 (February 1994): 133–46. http://dx.doi.org/10.1016/0029-5493(94)90325-5.

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8

Nath, Saheli. "Risk Shift: An Institutional Logics Perspective." Administration & Society 51, no. 7 (February 28, 2018): 1113–47. http://dx.doi.org/10.1177/0095399718760581.

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This study uses the concept of institutional logics and the framing processes emanating from these guiding logics to understand how risk is shifted through public policies. The study concludes that Hacker’s argument that public policies have reconstructed markets to aid the privileged by shifting risk onto the less privileged may have underestimated some of the complexities driving the phenomenon, particularly those stemming from actors having to cope with conflicting logics and ambiguity concerning policy solutions to seemingly intractable challenges. Risk shift does not necessarily involve unilateral transfer of risk from policy makers to risk bearers. Risk shift can emerge out of the complex microinteractions among relevant actors and the framing processes guided by competing logics or belief systems in which the collaborating actors are embedded.

9

Haimson, Chloe. "INTERACTIONAL RESISTANCE DURING BLACK LIVES MATTER PROTESTS: THE POLITICAL STAKES OF REBELLING AGAINST THE PUBLIC ORDER*." Mobilization: An International Quarterly 25, no. 2 (June 1, 2020): 185–200. http://dx.doi.org/10.17813/1086-671x-25-2-185.

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Drawing from ethnographic research, this study examines how interactions between protesters and police unfold at Black Lives Matter demonstrations in two cities with distinct policing regimes. From an analysis of contentious moments during these local movement protests, I argue that protesters in both cities consciously resist the terms of engagement set by police in an effort to demonstrate their overarching opposition to police violence and racism, and to illustrate that communities can police themselves while also seeking to avoid arrest or police violence. I call this protesters’ “interactional resistance” This type of resistance is predicated on protesters pushing the boundaries of the rules of engagement with the police while using their structural knowledge of the situation and likely police responses. Interactional resistance bolsters claims by local Black Lives Matters protest movements that communities can be self-policing. In contrast with prior research on policing of protests, a focus on interactional resistance emphasizes the actions and decisions of protesters, not just the police. It also shows how protesters manage to enact resistance even when they are trying to avoid arrest. Further, I also show that police responses to the same level of transgression vary depending on the local police-control norms practiced in a specific place. Overall, these microinteractions both point to and shape the structures of repression.

10

Kemper, Theodore D., and Randall Collins. "Dimensions of Microinteraction." American Journal of Sociology 96, no. 1 (July 1990): 32–68. http://dx.doi.org/10.1086/229492.

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11

Ponnada, Aditya, Caitlin Haynes, Dharam Maniar, Justin Manjourides, and Stephen Intille. "Microinteraction Ecological Momentary Assessment Response Rates." Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 1, no. 3 (September 11, 2017): 1–16. http://dx.doi.org/10.1145/3130957.

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12

Ponnada, Aditya, Jixin Li, Shirlene Wang, Wei-Lin Wang, Bridgette Do, Genevieve F. Dunton та Stephen S. Intille. "Contextual Biases in Microinteraction Ecological Momentary Assessment (μEMA) Non-response". Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 6, № 1 (29 березня 2022): 1–24. http://dx.doi.org/10.1145/3517259.

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Ecological momentary assessment (EMA) is used to gather in-situ self-report on behaviors using mobile devices. Microinteraction EMA (μEMA), is a type of EMA where each survey is only one single question that can be answered with a glanceable microinteraction on a smartwatch. Prior work shows that even when μEMA interrupts far more frequently than smartphone-EMA, μEMA yields higher response rates with lower burden. We examined the contextual biases associated with non-response of μEMA prompts on a smartwatch. Based on prior work on EMA non-response and smartwatch use, we identified 10 potential contextual biases from three categories: temporal (time of the day, parts of waking day, day of the week, and days in study), device use (screen state, charging status, battery mode, and phone usage), and activity (wrist motion and location). We used data from a longitudinal study where 131 participants (Mean age 22.9 years, SD = 3.0) responded to μEMA surveys on a smartwatch for at least six months. Using mixed-effects logistic regression, we found that all temporal, activity/mobility, and device use variables had a statistically significant (p<0.001) association with momentary μEMA non-response. We discuss the implication of these results for future use of context-aware μEMA methodology.

13

Ellis, Rachel. "Silent Disagreement: Microinteractional Solutions to Moral Dissent Among Catholic Converts." Journal for the Scientific Study of Religion 56, no. 2 (June 2017): 383–97. http://dx.doi.org/10.1111/jssr.12332.

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14

Furnari, Santi. "Interstitial Spaces: Microinteraction Settings and the Genesis of New Practices Between Institutional Fields." Academy of Management Review 39, no. 4 (October 2014): 439–62. http://dx.doi.org/10.5465/amr.2012.0045.

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15

Ponnada, Aditya, Shirlene Wang, Daniel Chu, Bridgette Do, Genevieve Dunton, and Stephen Intille. "Intensive Longitudinal Data Collection Using Microinteraction Ecological Momentary Assessment: Pilot and Preliminary Results." JMIR Formative Research 6, no. 2 (February 9, 2022): e32772. http://dx.doi.org/10.2196/32772.

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Background Ecological momentary assessment (EMA) uses mobile technology to enable in situ self-report data collection on behaviors and states. In a typical EMA study, participants are prompted several times a day to answer sets of multiple-choice questions. Although the repeated nature of EMA reduces recall bias, it may induce participation burden. There is a need to explore complementary approaches to collecting in situ self-report data that are less burdensome yet provide comprehensive information on an individual’s behaviors and states. A new approach, microinteraction EMA (μEMA), restricts EMA items to single, cognitively simple questions answered on a smartwatch with single-tap assessments using a quick, glanceable microinteraction. However, the viability of using μEMA to capture behaviors and states in a large-scale longitudinal study has not yet been demonstrated. Objective This paper describes the μEMA protocol currently used in the Temporal Influences on Movement & Exercise (TIME) Study conducted with young adults, the interface of the μEMA app used to gather self-report responses on a smartwatch, qualitative feedback from participants after a pilot study of the μEMA app, changes made to the main TIME Study μEMA protocol and app based on the pilot feedback, and preliminary μEMA results from a subset of active participants in the TIME Study. Methods The TIME Study involves data collection on behaviors and states from 246 individuals; measurements include passive sensing from a smartwatch and smartphone and intensive smartphone-based hourly EMA, with 4-day EMA bursts every 2 weeks. Every day, participants also answer a nightly EMA survey. On non–EMA burst days, participants answer μEMA questions on the smartwatch, assessing momentary states such as physical activity, sedentary behavior, and affect. At the end of the study, participants describe their experience with EMA and μEMA in a semistructured interview. A pilot study was used to test and refine the μEMA protocol before the main study. Results Changes made to the μEMA study protocol based on pilot feedback included adjusting the single-question selection method and smartwatch vibrotactile prompting. We also added sensor-triggered questions for physical activity and sedentary behavior. As of June 2021, a total of 81 participants had completed at least 6 months of data collection in the main study. For 662,397 μEMA questions delivered, the compliance rate was 67.6% (SD 24.4%) and the completion rate was 79% (SD 22.2%). Conclusions The TIME Study provides opportunities to explore a novel approach for collecting temporally dense intensive longitudinal self-report data in a sustainable manner. Data suggest that μEMA may be valuable for understanding behaviors and states at the individual level, thus possibly supporting future longitudinal interventions that require within-day, temporally dense self-report data as people go about their lives.

16

Deng, Hao, Chen Tian, Li Li, Yanjie Liang, Shengjun Yan, Ming Hu, Wenbin Xu, Zhang Lin, and Liyuan Chai. "Microinteraction Analysis between Heavy Metals and Coexisting Phases in Heavy Metal Containing Solid Wastes." ACS ES&T Engineering 2, no. 4 (January 10, 2022): 547–63. http://dx.doi.org/10.1021/acsestengg.1c00343.

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17

Ponnada, Aditya, Binod Thapa-Chhetry, Justin Manjourides, and Stephen Intille. "Measuring Criterion Validity of Microinteraction Ecological Momentary Assessment (Micro-EMA): Exploratory Pilot Study With Physical Activity Measurement." JMIR mHealth and uHealth 9, no. 3 (March 10, 2021): e23391. http://dx.doi.org/10.2196/23391.

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Background Ecological momentary assessment (EMA) is an in situ method of gathering self-report on behaviors using mobile devices. In typical phone-based EMAs, participants are prompted repeatedly with multiple-choice questions, often causing participation burden. Alternatively, microinteraction EMA (micro-EMA or μEMA) is a type of EMA where all the self-report prompts are single-question surveys that can be answered using a 1-tap glanceable microinteraction conveniently on a smartwatch. Prior work suggests that μEMA may permit a substantially higher prompting rate than EMA, yielding higher response rates and lower participation burden. This is achieved by ensuring μEMA prompt questions are quick and cognitively simple to answer. However, the validity of participant responses from μEMA self-report has not yet been formally assessed. Objective In this pilot study, we explored the criterion validity of μEMA self-report on a smartwatch, using physical activity (PA) assessment as an example behavior of interest. Methods A total of 17 participants answered 72 μEMA prompts each day for 1 week using a custom-built μEMA smartwatch app. At each prompt, they self-reported whether they were doing sedentary, light/standing, moderate/walking, or vigorous activities by tapping on the smartwatch screen. Responses were compared with a research-grade activity monitor worn on the dominant ankle simultaneously (and continuously) measuring PA. Results Participants had an 87.01% (5226/6006) μEMA completion rate and a 74.00% (5226/7062) compliance rate taking an average of only 5.4 (SD 1.5) seconds to answer a prompt. When comparing μEMA responses with the activity monitor, we observed significantly higher (P<.001) momentary PA levels on the activity monitor when participants self-reported engaging in moderate+vigorous activities compared with sedentary or light/standing activities. The same comparison did not yield any significant differences in momentary PA levels as recorded by the activity monitor when the μEMA responses were randomly generated (ie, simulating careless taps on the smartwatch). Conclusions For PA measurement, high-frequency μEMA self-report could be used to capture information that appears consistent with that of a research-grade continuous sensor for sedentary, light, and moderate+vigorous activity, suggesting criterion validity. The preliminary results show that participants were not carelessly answering μEMA prompts by randomly tapping on the smartwatch but were reporting their true behavior at that moment. However, more research is needed to examine the criterion validity of μEMA when measuring vigorous activities.

18

Hou, Jinju, Shudong Zhang, Xiaotong Zhang, Kainan Wang, Qiuzhuo Zhang, and Yuhan Shi. "Insights into ferulic acid detoxification mechanism by using a novel adsorbent, AEPA250: The microinteraction of ferulic acid with AEPA250 and Saccharomyces cerevisiae." Journal of Hazardous Materials 415 (August 2021): 125685. http://dx.doi.org/10.1016/j.jhazmat.2021.125685.

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19

Gonzales, Sara, Matthew B. Carson, Guillaume Viger, Lisa O'Keefe, Norrina B. Allen, Joseph P. Ferrie, and Kristi Holmes. "User Testing with Microinteractions." Information Technology and Libraries 40, no. 1 (March 11, 2021). http://dx.doi.org/10.6017/ital.v40i1.12341.

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Enabling and supporting discoverability of research outputs and datasets are key functions of university and academic health center institutional repositories. Yet adoption rates among potential repository users are hampered by a number of factors, prominent among which are difficulties with basic usability. In their efforts to implement a local instance of InvenioRDM, a turnkey next generation repository, team members at Northwestern University’s Galter Health Sciences Library & Learning Center supplemented agile development principles and methods and a user experience design-centered approach with observations of users’ microinteractions (interactions with each part of the software’s interface that requires human intervention). Microinteractions were observed through user testing sessions conducted in Fall 2019. The result has been a more user-informed development effort incorporating the experiences and viewpoints of a multidisciplinary team of researchers spanning multiple departments of a highly ranked research university.

20

Ma, Jia Yang, and Chun‐Ching Chen. "Evaluating user perception and emotion of microinteractions using a contradictory semantic scale." Journal of the Society for Information Display, August 13, 2021. http://dx.doi.org/10.1002/jsid.1075.

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21

Betz, Sonya, and Robyn Hall. "Self-Archiving with Ease in an Institutional Repository: Microinteractions and the User Experience." Information Technology and Libraries 34, no. 3 (September 24, 2015). http://dx.doi.org/10.6017/ital.v34i3.5900.

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22

Husu, Hanna-Mari. "Loneliness and interaction ritual theory: failed interaction chains among Finnish university students." Emotions and Society, 2021. http://dx.doi.org/10.1332/263169020x16065613191228.

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This article relates loneliness to interaction ritual theory, understanding loneliness in terms of problematic microinteractional dynamics. The advantage of interaction ritual theory is that it extends our understanding of the issue of the psychologised self and related questions such as how loneliness feels or is experienced. Loneliness is here defined as a response to interaction representing relational understanding of emotions. Interaction ritual theory is interested in the emotional consequences that individuals experience from successful or unsuccessful interaction rituals. Loneliness in this view represents a state in which the individual is denied access to rewarding aspects of interaction. This study is based on 32 lifecourse interviews with Finnish students. It finds that loneliness as a failed microinteractional dynamic originates from students’ previous negative experiences of interaction, problematic situational settings and the structured flow of students’ daily activities.

23

Marcucci, Olivia, and Rowhea Elmesky. "Advancing Culturally Relevant Discipline: An Ethnographic Microanalysis of Disciplinary Interactions With Black Students." Urban Education, March 20, 2020, 004208592090916. http://dx.doi.org/10.1177/0042085920909165.

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Culturally relevant discipline (CRD) has the potential to mitigate the disproportionate disciplining of Black students in American schools. Utilizing interaction ritual theory, this research uses ethnographic microanalysis to investigate nonverbal, paraverbal, and verbal communication in three student–teacher disciplinary interactions from one predominately Black high school. The analysis (a) provides the first microlevel empirical evidence of the success of culturally relevant discipline. Then it uses microinteractional evidence to resolve theoretical neglect and strengthen theoretical assertions of past CRD scholarship. It argues that (b) CRD can reinforce learning processes and (c) critical consciousness is a teacher prerequisite for CRD.

24

Givan, Benjamin. "Rethinking Interaction in Jazz Improvisation." Music Theory Online 22, no. 3 (September 2016). http://dx.doi.org/10.30535/mto.22.3.7.

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In recent years, the notion that “good jazz improvisation is sociable and interactive just like a conversation” (Monson 1996, 84) has become near-conventional wisdom in jazz scholarship. This paper revisits this assumption and considers some cases in which certain sorts of interactions may not always be present or desirable in jazz performance. Three types of improvised interaction are defined: (1) “microinteraction,” which occurs at a very small scale (e.g. participatory discrepancies) and is not specific to jazz; (2) “macrointeraction,” which concerns general levels of musical intensity; and (3) “motivic interaction”—players exchanging identifiable motivic figures—which is a chief concern of today’s jazz researchers. Further, motivic interaction can be either dialogic, when two or more musicians interact with one another, or monologic, when one player pursues a given musical strategy and others respond but the first player does not reciprocate (as in “call and response”). The paper concludes by briefly considering some of the reasons for, and implications of, the emergence of interaction-oriented jazz scholarship during the late twentieth century.