-
Xie, B.; He, D.; Mercer, T.; Wang, Y.; Wu, D.; Fleischmann, K.R.; Zhang, Y.; Yoder, L.H.; Stephens, K.K.; Mackert, M.; Lee, M.K.: Global health crises are also information crises : a call to action (2020)
0.00
0.0023678814 = product of:
0.0047357627 = sum of:
0.0047357627 = product of:
0.009471525 = sum of:
0.009471525 = weight(_text_:a in 32) [ClassicSimilarity], result of:
0.009471525 = score(doc=32,freq=8.0), product of:
0.053105544 = queryWeight, product of:
1.153047 = idf(docFreq=37942, maxDocs=44218)
0.046056706 = queryNorm
0.17835285 = fieldWeight in 32, product of:
2.828427 = tf(freq=8.0), with freq of:
8.0 = termFreq=8.0
1.153047 = idf(docFreq=37942, maxDocs=44218)
0.0546875 = fieldNorm(doc=32)
0.5 = coord(1/2)
0.5 = coord(1/2)
- Abstract
- In this opinion paper, we argue that global health crises are also information crises. Using as an example the coronavirus disease 2019 (COVID-19) epidemic, we (a) examine challenges associated with what we term "global information crises"; (b) recommend changes needed for the field of information science to play a leading role in such crises; and (c) propose actionable items for short- and long-term research, education, and practice in information science.
- Type
- a
-
Slota, S.C.; Fleischmann, K.R.; Lee, M.K.; Greenberg, S.R.; Nigam, I.; Zimmerman, T.; Rodriguez, S.; Snow, J.: ¬A feeling for the data : how government and nonprofit stakeholders negotiate value conflicts in data science approaches to ending homelessness (2023)
0.00
0.0020296127 = product of:
0.0040592253 = sum of:
0.0040592253 = product of:
0.008118451 = sum of:
0.008118451 = weight(_text_:a in 969) [ClassicSimilarity], result of:
0.008118451 = score(doc=969,freq=8.0), product of:
0.053105544 = queryWeight, product of:
1.153047 = idf(docFreq=37942, maxDocs=44218)
0.046056706 = queryNorm
0.15287387 = fieldWeight in 969, product of:
2.828427 = tf(freq=8.0), with freq of:
8.0 = termFreq=8.0
1.153047 = idf(docFreq=37942, maxDocs=44218)
0.046875 = fieldNorm(doc=969)
0.5 = coord(1/2)
0.5 = coord(1/2)
- Abstract
- Governmental and organizational policy increasingly claims to be data-driven, data-informed, or knowledge-driven. We explore the data practices of local governments and nonprofits a seeking to end homelessness in the City of Austin. Drawing on 31 interviews with stakeholders, alongside the reflections and experiences of our interdisciplinary, cross-sector collaborative team, we consider the role of data in guiding and informing interventions and policy regarding homelessness. Ending homelessness is a particularly challenging scenario for intervention, with increasing politicization, changing circumstances, and needing rapid intervention to reduce harm. In exploring some implications of data science "in the wild" as it is deployed, understood, and supported within the Travis County Continuum of Care (CoC), we analyze how data-intensive work connects and engages across disciplinary boundaries. Furthermore, we consider how data science and the iField can collaborate in addressing complex, social problems as advisors and partners with invested organizations.
- Type
- a
-
Verma, N.; Fleischmann, K.R.; Zhou, L.; Xie, B.; Lee, M.K.; Rich, K.; Shiroma, K.; Jia, C.; Zimmerman, T.: Trust in COVID-19 public health information (2022)
0.00
0.0014647468 = product of:
0.0029294936 = sum of:
0.0029294936 = product of:
0.005858987 = sum of:
0.005858987 = weight(_text_:a in 771) [ClassicSimilarity], result of:
0.005858987 = score(doc=771,freq=6.0), product of:
0.053105544 = queryWeight, product of:
1.153047 = idf(docFreq=37942, maxDocs=44218)
0.046056706 = queryNorm
0.11032722 = fieldWeight in 771, product of:
2.4494898 = tf(freq=6.0), with freq of:
6.0 = termFreq=6.0
1.153047 = idf(docFreq=37942, maxDocs=44218)
0.0390625 = fieldNorm(doc=771)
0.5 = coord(1/2)
0.5 = coord(1/2)
- Abstract
- Understanding the factors that influence trust in public health information is critical for designing successful public health campaigns during pandemics such as COVID-19. We present findings from a cross-sectional survey of 454 US adults-243 older (65+) and 211 younger (18-64) adults-who responded to questionnaires on human values, trust in COVID-19 information sources, attention to information quality, self-efficacy, and factual knowledge about COVID-19. Path analysis showed that trust in direct personal contacts (B = 0.071, p = .04) and attention to information quality (B = 0.251, p < .001) were positively related to self-efficacy for coping with COVID-19. The human value of self-transcendence, which emphasizes valuing others as equals and being concerned with their welfare, had significant positive indirect effects on self-efficacy in coping with COVID-19 (mediated by attention to information quality; effect = 0.049, 95% CI 0.001-0.104) and factual knowledge about COVID-19 (also mediated by attention to information quality; effect = 0.037, 95% CI 0.003-0.089). Our path model offers guidance for fine-tuning strategies for effective public health messaging and serves as a basis for further research to better understand the societal impact of COVID-19 and other public health crises.
- Type
- a
-
Slota, S.C.; Fleischmann, K.R.; Greenberg, S.; Verma, N.; Cummings, B.; Li, L.; Shenefiel, C.: Locating the work of artificial intelligence ethics (2023)
0.00
0.0010148063 = product of:
0.0020296127 = sum of:
0.0020296127 = product of:
0.0040592253 = sum of:
0.0040592253 = weight(_text_:a in 899) [ClassicSimilarity], result of:
0.0040592253 = score(doc=899,freq=2.0), product of:
0.053105544 = queryWeight, product of:
1.153047 = idf(docFreq=37942, maxDocs=44218)
0.046056706 = queryNorm
0.07643694 = fieldWeight in 899, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
1.153047 = idf(docFreq=37942, maxDocs=44218)
0.046875 = fieldNorm(doc=899)
0.5 = coord(1/2)
0.5 = coord(1/2)
- Type
- a
