Journal articles: 'Scant data'

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O'Brien, Claire. "Scant Data Cause Widespread Concern." Science 271, no. 5257 (March 29, 1996): 1798. http://dx.doi.org/10.1126/science.271.5257.1798-a.

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Jang, Mingyu, Geunbae Kim, Dongyeong Kim, and Dongweon Yoon. "Blind Interleaver Parameter Estimation From Scant Data." IEEE Access 8 (2020): 217282–89. http://dx.doi.org/10.1109/access.2020.3041795.

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MOON, MARY ANN. "Device Approvals Often Based on Scant Data." Family Practice News 40, no. 2 (February 2010): 12. http://dx.doi.org/10.1016/s0300-7073(10)70109-2.

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Ansell, Judith. "Inter-assessor variability: scant data proves the point." Developmental Medicine & Child Neurology 58, no. 2 (January 21, 2016): 111. http://dx.doi.org/10.1111/dmcn.13023.

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O'Brien, C. "Mad Cow Disease: Scant Data Cause Widespread Concern." Science 271, no. 5257 (March 29, 1996): 1798–0. http://dx.doi.org/10.1126/science.271.5257.1798.

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O'Brien, C. "Mad Cow Disease: Scant Data Cause Widespread Concern." Science 271, no. 5257 (March 29, 1996): 1798a—1798. http://dx.doi.org/10.1126/science.271.5257.1798a.

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EVANS, JEFF. "Data Scant on Tx for Young Opioid Abusers." Clinical Psychiatry News 34, no. 3 (March 2006): 42. http://dx.doi.org/10.1016/s0270-6644(06)71253-x.

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Mosher, Donald L. "The Self and Masochism: Loose Theory and Scant Data." Contemporary Psychology: A Journal of Reviews 35, no. 6 (June 1990): 550–51. http://dx.doi.org/10.1037/028684.

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Erikson, Jane. "10-YearReviewof rials Finds Scant Data on Race or Ethnicity." Oncology Times 24, no. 12 (December 2002): 61–62. http://dx.doi.org/10.1097/01.cot.0000289352.10983.4a.

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Alves, Davi Mello Cunha Crescente, Anderson Aires Eduardo, Eduardo Vinícius da Silva Oliveira, Fabricio Villalobos, Ricardo Dobrovolski, Taiguã Corrêa Pereira, Adauto de Souza Ribeiro, et al. "Unveiling geographical gradients of species richness from scant occurrence data." Global Ecology and Biogeography 29, no. 4 (January 9, 2020): 748–59. http://dx.doi.org/10.1111/geb.13055.

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MOON, MARY ANN. "FDA Approval of Heart Devices Often Based on Scant Data." Internal Medicine News 43, no. 2 (February 2010): 20. http://dx.doi.org/10.1016/s1097-8690(10)70089-5.

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DAGANI, RON. "Data on MIC's Toxicity Are Scant, Leave Much To Be Learned." Chemical & Engineering News 63, no. 6 (February 11, 1985): 37–40. http://dx.doi.org/10.1021/cen-v063n006.p037.

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Koninckx, Philippe R., Anastasia Ussia, Errico Zupi, and Victor Gomel. "Association of Endometriosis and Adenomyosis: Vast Literature but Scant Conclusive Data." Journal of Minimally Invasive Gynecology 25, no. 5 (July 2018): 745–48. http://dx.doi.org/10.1016/j.jmig.2018.03.012.

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Chakravarthy, Adithi D., Dilanga Abeyrathna, Mahadevan Subramaniam, Parvathi Chundi, and Venkataramana Gadhamshetty. "Semantic Image Segmentation Using Scant Pixel Annotations." Machine Learning and Knowledge Extraction 4, no. 3 (July 1, 2022): 621–40. http://dx.doi.org/10.3390/make4030029.

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The success of deep networks for the semantic segmentation of images is limited by the availability of annotated training data. The manual annotation of images for segmentation is a tedious and time-consuming task that often requires sophisticated users with significant domain expertise to create high-quality annotations over hundreds of images. In this paper, we propose the segmentation with scant pixel annotations (SSPA) approach to generate high-performing segmentation models using a scant set of expert annotated images. The models are generated by training them on images with automatically generated pseudo-labels along with a scant set of expert annotated images selected using an entropy-based algorithm. For each chosen image, experts are directed to assign labels to a particular group of pixels, while a set of replacement rules that leverage the patterns learned by the model is used to automatically assign labels to the remaining pixels. The SSPA approach integrates active learning and semi-supervised learning with pseudo-labels, where expert annotations are not essential but generated on demand. Extensive experiments on bio-medical and biofilm datasets show that the SSPA approach achieves state-of-the-art performance with less than 5% cumulative annotation of the pixels of the training data by the experts.

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Jung, Yongseok, Mingyu Jang, and Dongweon Yoon. "Improved Method for Blind Interleaver Parameter Estimation Using Matrix Multiplication From Scant Data." IEEE Access 9 (2021): 138209–14. http://dx.doi.org/10.1109/access.2021.3117869.

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Jung, Yongseok, Mingyu Jang, and Dongweon Yoon. "Improved Method for Blind Interleaver Parameter Estimation Using Matrix Multiplication From Scant Data." IEEE Access 9 (2021): 138209–14. http://dx.doi.org/10.1109/access.2021.3117869.

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Bigi, Velia, Alessandro Pezzoli, Elena Comino, and Maurizio Rosso. "A Vulnerability Assessment in Scant Data Context: The Case of North Horr Sub-County." Sustainability 12, no. 15 (July 27, 2020): 6024. http://dx.doi.org/10.3390/su12156024.

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In Kenyan rural areas belonging to the Arid and Semi-Arid Lands (ASALs), water quantity and water quality are major issues for the local population. In North Horr Sub-County water quality is threatened by nitrate contamination due to fecal matter pollution. This research, hence, aims at assessing the vulnerability of open shallow water sources to nitrate contamination due to fecal intrusion following flooding events and nitrate percolation in groundwater. The present research, indeed, provides, on one hand, new insights into the analysis of the vulnerability in a scant data context; on the other hand, it assesses the adaptation measures contained in the local development plan. Applying the reference definition of the Intergovernmental Panel on Climate Change (IPCC), the results demonstrate that the open shallow water sources in the northern part of the sub-county are more vulnerable to nitrate contamination. Furthermore, the consistency of the results proves the suitability of the methodology selected. Understanding the vulnerability at the local scale is key to planning risk-reduction strategies as well to increasing the local population’s knowledge about flood-related risks and water quality.

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Lee Chee Hang, Lee Chee Hang, Yu-Beng Leau Lee Chee Hang, Yong Jin Park Yu-Beng Leau, Zhiwei Yan Yong Jin Park, and Supriyanto Praptodiyono Zhiwei Yan. "Protocol and Evaluation of Network Mobility with Producer Nodes in Named Data Networking." 網際網路技術學刊 23, no. 3 (May 2022): 459–66. http://dx.doi.org/10.53106/160792642022052303004.

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The drawbacks of the current TCP/IP suits have been pointed out. However, Named Data Networking (NDN) has some limitations, the most notable of which is producer and network mobility. Mainly, producer mobility in moving networks receives scant attention. There are numerous issues that the NDN must address before it can be used by the public, one of which is mobility. In NDN, consumer mobility is naturally supported, but producer mobility is not. The latter is researched a lot, but few results have been reported regarding network mobility with producers. In this paper, two approaches will be focused on: the Hybrid Network Mobility (Hybrid NeMo) approach and the Network Mobility (NeMoI). These two approaches are being compared because they both employed similar techniques for managing network mobility. Furthermore, they will be compared using the same topology to allow more accurate comparisons of their signalling cost and data delivery cost.

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Kennedy, Brianna L., and Amanda Datnow. "Student Involvement and Data-Driven Decision Making." Youth & Society 43, no. 4 (December 1, 2010): 1246–71. http://dx.doi.org/10.1177/0044118x10388219.

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Existing literature supports the inclusion of students in education reform, documenting benefits for both students and educators. When student voice is not included in reform efforts, these efforts are more likely to flounder. The emerging educational reform of data-driven decision making (DDDM) offers promise for increasing student achievement. However, scant research documents the involvement of students in DDDM reforms. Using a theoretical framework that advocates for democratically involving students in education reform, this cross-case analysis examines the role of students in DDDM reforms in elementary and high schools known to be exemplars of data-driven decision making. Based on findings of efforts made by exemplar districts as well as actions they did not take to involve students, the authors conclude that a new typology is necessary for assessing student involvement in DDDM. Consequently, the authors propose a new three-tiered typology for conceptualizing this phenomenon.

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B, Subramanyam, and Iswarya R. "Troubled Projects in Construction Due To Scant Risk Management." International Journal of Engineering & Technology 7, no. 3.12 (July 20, 2018): 322. http://dx.doi.org/10.14419/ijet.v7i3.12.16050.

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This paper will focus on troubled projects in construction due to inadequate and insufficient risk management. Inadequate risk management has the ability to severely impact construction project. The main objective of the present paper is to attempt a composition of already known risk management process, at such way that it can be applied by the modern enterprises that deal with the undertaking or/and implementation of constructional work. This paper describes about the main sources for the failure of a construction project such as no initial risk assessment, inadequate documentation and tracking, irregular & incomplete status reporting, failure to define parameters etc. The methodology contains examining existing data, results and created a checklist for all those who are involved in construction project disasters. It can be applied at all stages in the project cycle, from the earliest assessments of strategy to initiation, planning, implementation and closure. Risk management will also provide advantages in better accountability and justification of decisions, by providing a well-suited and robust process that supports decision-making.

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Plum, Fabian, and David Labonte. "scAnt—an open-source platform for the creation of 3D models of arthropods (and other small objects)." PeerJ 9 (April 12, 2021): e11155. http://dx.doi.org/10.7717/peerj.11155.

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We present scAnt, an open-source platform for the creation of digital 3D models of arthropods and small objects. scAnt consists of a scanner and a Graphical User Interface, and enables the automated generation of Extended Depth Of Field images from multiple perspectives. These images are then masked with a novel automatic routine which combines random forest-based edge-detection, adaptive thresholding and connected component labelling. The masked images can then be processed further with a photogrammetry software package of choice, including open-source options such as Meshroom, to create high-quality, textured 3D models. We demonstrate how these 3D models can be rigged to enable realistic digital specimen posing, and introduce a novel simple yet effective method to include semi-realistic representations of approximately planar and transparent structures such as wings. As a result of the exclusive reliance on generic hardware components, rapid prototyping and open-source software, scAnt costs only a fraction of available comparable systems. The resulting accessibility of scAnt will (i) drive the development of novel and powerful methods for machine learning-driven behavioural studies, leveraging synthetic data; (ii) increase accuracy in comparative morphometric studies as well as extend the available parameter space with area and volume measurements; (iii) inspire novel forms of outreach; and (iv) aid in the digitisation efforts currently underway in several major natural history collections.

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Stern, Michael J., Alison E. Adams, and Jeffrey Boase. "Rural Community Participation, Social Networks, and Broadband Use: Examples from Localized and National Survey Data." Agricultural and Resource Economics Review 40, no. 2 (September 2011): 158–71. http://dx.doi.org/10.1017/s106828050000798x.

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Although attention has been given to how broadband access is related to economic development in rural areas, scant consideration has been given to how it may be associated with voluntary participation. This issue is important in that numerous studies have shown how much more vital community participation is in rural areas as compared to suburban and urban places. Drawing on three diverse data sets, we examine the influence of broadband access on community participation. In addition, we explore whether broadband access exerts its influence through, in conjunction with, or independent of social networks. The results suggest that broadband access and social network size have independent effects on volunteering in rural places.

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Lacitignola, Luca, Rossella Samarelli, Nicola Zizzo, Elena Circella, Claudia Acquafredda, Marzia Stabile, Roberto Lombardi, Francesco Staffieri, and Antonio Camarda. "CT Findings and Histological Evaluation of Red Foxes (Vulpes vulpes) with Chronic Head Trauma Injury: A Retrospective Study." Animals 11, no. 4 (April 3, 2021): 1010. http://dx.doi.org/10.3390/ani11041010.

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Large numbers of wild animals are injured every year in road traffic accidents. Scant data are available for rescued wild carnivores, in particular for red foxes. Cases of foxes with head trauma were retrospectively considered for inclusion in this study. Clinical examination, modified Glasgow coma scale (MGCS), computed tomography (CT) examination, therapy, outcome, and post mortem findings of the brain were investigated. In all foxes, cranial vaults lesion occurred in single (67%) or multiple sites (33%). Midline shift and hydrocephalus were observed in this population. The mean survival was 290 (±176) days. In our study, we performed CT scans on average 260 days after fox rescue, and we speculate that persisting clinical signs could be attributed to TBI. In our study, only two foxes were alive at the time of writing. Other foxes were euthanized due to the severity of the clinical signs. CT scans help diagnose chronic lesions and their effect on prognostic judgment for animals released to wildlife environments.

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Stumpf, Patrick Simon, Lisa-Katrin Schätzle, and Andreas Schuppert. "Transferlernen in der Biomedizin." BIOspektrum 26, no. 6 (October 14, 2020): 682–84. http://dx.doi.org/10.1007/s12268-020-1459-2.

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Abstract Machine learning is commonly employed to extract meaningful information from large and complex data. In situations where only scant data is available, algorithms can leverage abundant data from a separate (unrelated) context to address the learning problem. Here, we present two recently developed biomedical applications that take advantage of transfer learning to bridge the gap from model systems to human: single-cell label transfer and drug response prediction in patients.

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Onwuegbuzie, Anthony J., Wendy B. Dickinson, Nancy L. Leech, and Annmarie G. Zoran. "A Qualitative Framework for Collecting and Analyzing Data in Focus Group Research." International Journal of Qualitative Methods 8, no. 3 (September 2009): 1–21. http://dx.doi.org/10.1177/160940690900800301.

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Despite the abundance of published material on conducting focus groups, scant specific information exists on how to analyze focus group data in social science research. Thus, the authors provide a new qualitative framework for collecting and analyzing focus group data. First, they identify types of data that can be collected during focus groups. Second, they identify the qualitative data analysis techniques best suited for analyzing these data. Third, they introduce what they term as a micro-interlocutor analysis, wherein meticulous information about which participant responds to each question, the order in which each participant responds, response characteristics, the nonverbal communication used, and the like is collected, analyzed, and interpreted. They conceptualize how conversation analysis offers great potential for analyzing focus group data. They believe that their framework goes far beyond analyzing only the verbal communication of focus group participants, thereby increasing the rigor of focus group analyses in social science research.

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Siebers, Albertus G., Paul JJM Klinkhamer, Judith EM Vedder, Marc Arbyn, and Johan Bulten. "Causes and Relevance of Unsatisfactory and Satisfactory but Limited Smears of Liquid-Based Compared With Conventional Cervical Cytology." Archives of Pathology & Laboratory Medicine 136, no. 1 (January 1, 2012): 76–83. http://dx.doi.org/10.5858/arpa.2011-0113-oa.

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Context.—Recent randomized controlled trials have shown a significant decrease in unsatisfactory rates for liquid-based cytology (LBC) compared with conventional Papanicolaou test (CP). The underlying causes and relevance of unsatisfactory results for LBC and CP have never been compared within the setting of a randomized controlled trial. Objective.—To examine differences in causes and relevance of unsatisfactory and satisfactory but limited by (SBLB) results for LBC and CP. Design.—Data from the Netherlands ThinPrep Versus Conventional Cytology (NETHCON) trial were used, involving 89 784 women. Causes and relevance of unsatisfactory and SBLB results were analyzed. Results.—The primary cause for unsatisfactory results for CP and LBC was scant cellularity. Other causes for unsatisfactory CPs were virtually eliminated with LBC. The same was true for SBLB subcategories, with the exception of SBLB absence of transformation zone component and SBLB scant cellularity. The SBLB absence of transformation zone component showed a statistically significant 22% and SBLB scant cellularity a 12% nonsignificant increase with LBC. The detection rates of abnormalities found during 18 months of follow-up of unsatisfactory test results did not differ significantly between the 2 study arms, nor did they differ from the initial test positivity rates from the NETHCON trial. Conclusions.—Liquid-based cytology shows an almost complete elimination of most causes for unsatisfactory CP, with scant cellularity remaining as the sole cause for unsatisfactory LBC. On the other hand, with LBC a significant increase of smears without a transformation zone component was noted. Women with an unsatisfactory test result are not at increased risk for cervical abnormalities either with LBC or with CP. Trial Registration.—Nederlands Trial Register, NTR1032, www.trialregister.nl.

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Gottfried, Anne, Caroline Hartmann, and Donald Yates. "Mining Open Government Data for Business Intelligence Using Data Visualization: A Two-Industry Case Study." Journal of Theoretical and Applied Electronic Commerce Research 16, no. 4 (March 18, 2021): 1042–65. http://dx.doi.org/10.3390/jtaer16040059.

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The business intelligence (BI) market has grown at a tremendous rate in the past decade due to technological advancements, big data and the availability of open source content. Despite this growth, the use of open government data (OGD) as a source of information is very limited among the private sector due to a lack of knowledge as to its benefits. Scant evidence on the use of OGD by private organizations suggests that it can lead to the creation of innovative ideas as well as assist in making better informed decisions. Given the benefits but lack of use of OGD to generate business intelligence, we extend research in this area by exploring how OGD can be used to generate business intelligence for the identification of market opportunities and strategy formulation; an area of research that is still in its infancy. Using a two-industry case study approach (footwear and lumber), we use latent Dirichlet allocation (LDA) topic modeling to extract emerging topics in these two industries from OGD, and a data visualization tool (pyLDAVis) to visualize the topics in order to interpret and transform the data into business intelligence. Additionally, we perform an environmental scanning of the environment for the two industries to validate the usability of the information obtained. The results provide evidence that OGD can be a valuable source of information for generating business intelligence and demonstrate how topic modeling and visualization tools can assist organizations in extracting and analyzing information for the identification of market opportunities.

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ZOGARIS, S., and U. DUSSLING. "On the occurrence of the Bull Ray Pteromylaeus bovinus (Chondrichthyes: Myliobatidae) in the Amvrakikos Gulf, Greece." Mediterranean Marine Science 11, no. 1 (April 23, 2010): 177. http://dx.doi.org/10.12681/mms.100.

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We document in this note the occurrence of the Bull Ray Pteromylaeus bovinus (Geoffroy St-Hilaire, 1817) (Chondrichthyes: Myliobatidae) in the Amvrakikos Gulf (eastern Ionian Sea), within a recently designated Wetlands National Park. Although distributional data for this species are scant, there is circumstantial evidence depicting the species as rare in Greece and the Mediterranean.

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Hoffman, Leon. "On the Clinical Utility of the Concept of Depressive Affect as Signal Affect." Journal of the American Psychoanalytic Association 40, no. 2 (April 1992): 405–23. http://dx.doi.org/10.1177/000306519204000205.

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The author reviews the scant literature relating to the concept of depressive affect as an affect parallel to anxiety. Then, through the presentation of detailed clinical psychoanalytic data, in particular the patient's associations to interpretation, he demonstrates the value to the conduct of a psychoanalysis of an awareness of the role of depressive affect as a signal affect that triggers defense.

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Mehta, Ansh. "Emotion Detection using Social Media Data." International Journal for Research in Applied Science and Engineering Technology 9, no. 11 (November 30, 2021): 1456–59. http://dx.doi.org/10.22214/ijraset.2021.39027.

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Abstract: Previous research on emotion recognition of Twitter users centered on the use of lexicons and basic classifiers on pack of words models, despite the recent accomplishments of deep learning in many disciplines of natural language processing. The study's main question is if deep learning can help them improve their performance. Because of the scant contextual information that most posts offer, emotion analysis is still difficult. The suggested method can capture more emotion sematic than existing models by projecting emoticons and words into emoticon space, which improves the performance of emotion analysis. In a microblog setting, this aids in the detection of subjectivity, polarity, and emotion. It accomplishes this by utilizing hash tags to create three large emotion-labeled data sets that can be compared to various emotional orders. Then compare the results of a few words and character-based repetitive and convolutional neural networks to the results of a pack of words and latent semantic indexing models. Furthermore, the specifics examine the transferability of the most recent hidden state representations across distinct emotional classes and whether it is possible to construct a unified model for predicting each of them using a common representation. It's been shown that repetitive neural systems, especially character-based ones, outperform pack-of-words and latent semantic indexing models. The semantics of the token must be considered while classifying the tweet emotion. The semantics of the tokens recorded in the hash map may be simply searched. Despite these models' low exchange capacities, the recently presented training heuristic produces a unity model with execution comparable to the three solo models. Keywords: Hashtags, Sentiment Analysis, Facial Recognition, Emotions.

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Zolala, Farzaneh. "Data collection after massive natural disasters (focusing on Bam earthquake, Iran)." Disaster Prevention and Management: An International Journal 19, no. 5 (November 9, 2010): 541–47. http://dx.doi.org/10.1108/09653561011091878.

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PurposeThe aim of this study is to explore mortality data collection after a destructive earthquake in Bam, Iran.Design/methodology/approachThis is a case study of mortality data collection using a qualitative approach. The study data were collected through interviews with people involved with data collection and processing in Iran, and an evaluation of routinely collected data.FindingsThe results indicated that there were many limitations affecting data collection after the earthquake. These limitations are rooted in basic problems within the existing data collection system and a lack of co‐ordination between the groups collecting data, including national and international aid groups that provided help after the earthquake.Research limitations/implicationsThe research is based on a very large and destructive earthquake; the results may be different for other natural disasters such as floods.Practical implicationsThe main target group of this study is the decision makers involved with the disaster relief issues at national and international levels. This issue of data collection is imperative for future disaster aid.Originality/valueThe study highlights the problems affecting routine collection of mortality data after a disaster, arising from the scant attention paid to proper documentation.

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Zhang, Hua, and Shaofeng Yuan. "How and When Does Big Data Analytics Capability Boost Innovation Performance?" Sustainability 15, no. 5 (February 22, 2023): 4036. http://dx.doi.org/10.3390/su15054036.

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The diffusion of big data in recent years has stimulated many companies to develop big data analytics capability (BDAC) to boost innovation performance. However, research regarding how and when BDAC can increase innovation performance is still scant. This study aims to test how (i.e., the mediating role of strategic flexibility and strategic innovation) and when (i.e., the moderating role of environmental uncertainty) BDAC can boost a firm’s innovation performance drawing on resource-based theory. Through a survey of 421 Chinese managers and employees who are engaged in the field of big data analytics, this study reveals that (1) BDAC has a positive effect on innovation performance, (2) strategic flexibility and strategic innovation play a significant serial mediating role in this relationship, and (3) the positive effect of BDAC on innovation performance is more significant under high (vs. low) environmental uncertainty conditions. This study contributes to the extant literature by verifying how BDAC can increase a firm’s innovation performance through the serial mediating role of strategic flexibility and strategic innovation. It also confirms a contingent factor (i.e., environmental uncertainty) regarding the positive effect of BDAC on innovation performance.

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Beseler, Cheryl L., and Risto H. Rautiainen. "Assessing Nonresponse Bias in Farm Injury Surveillance Data." Journal of Agricultural Safety and Health 27, no. 4 (2021): 215–27. http://dx.doi.org/10.13031/jash.14554.

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HighlightsDespite a response rate of about 18%, there was scant evidence of nonresponse bias.Farm and ranch characteristics of operations responding to a mailed survey were similar to those not responding.Responders were significantly more likely to be married but only slightly older and more educated than nonresponders.Earlier survey responders reported more injuries and greater severity when injured compared to later responders.Abstract. Nonresponse bias in a survey can result in misleading estimates of agricultural injuries and can misdirect prevention efforts aimed at reducing the burden of injuries on farmers. Responders (n = 2,977) and nonresponders (n = 13,849) were compared based on demographics and agricultural production characteristics to identify underrepresented subgroups. Injury characteristics were compared between early (n = 1,667) and late (n = 1,309) responders. Methods accounted for correlated data, sample size inflation of p-values, and assessment of meaningful differences. Few differences were identified between responders and nonresponders. Responders differed from nonresponders by state of residence, and responders were more likely to be married. Other characteristics (age, gender, education, farm size, crops grown, animals raised) were similar across groups. Early responders reported more injuries and more often sought medical care for an injury than late responders. The differences identified between responders and nonresponders were minimal and not likely to create bias. Differential reporting of injury and injury severity between early and late responders is worthy of further investigation. Keywords: Agriculture, Epidemiologic methods, Farm, Injury, Nonresponse bias, Occupational health, Ranch, Safety, Surveillance, Survey.

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Weinbaum, Rebecca K., and Anthony J. Onwuegbuzie. "Getting More Out of Your Interview Data: Toward a Framework for Debriefing the Transcriber of Interviews." Journal of Educational Issues 2, no. 1 (May 14, 2016): 248. http://dx.doi.org/10.5296/jei.v2i1.9216.

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In most qualitative research studies involving the creation of interview transcriptions, researchers seldom demonstrate much reflexivity about the transcription process, rarely making mention of transcription processes as part of their reporting of data collection and analysis procedures beyond a simple statement that audio- or videotaped data were transcribed. Disturbingly, although transcription is a part of the qualitative analysis process, transcription as a research method has received scant attention in the qualitative research literature. Thus, the purpose of this article was to provide a framework for debriefing the transcriber. As part of this framework, we have designed questions for the researcher to ask the transcriber to address representation and legitimation and also to facilitate movement into a deeper investigation. Finally, we present three examples of works from the extant literature wherein the transcriber was debriefed.

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Keuleers, Bertold, Geert Wets, Harry Timmermans, Theo Arentze, and Koen Vanhoof. "Stationary and Time-Varying Patterns in Activity Diary Panel Data: Explorative Analysis with Association Rules." Transportation Research Record: Journal of the Transportation Research Board 1807, no. 1 (January 2002): 9–15. http://dx.doi.org/10.3141/1807-02.

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The question of identifying temporal patterns in activity diary data has received only scant attention in the transportation literature, but interest is rapidly increasing. Most of the existing research uses well-known econometric methods to quantify change. Use of association rules to explore activity diary panel data, involving two waves, for possible stationary and time-varying patterns in activity-travel patterns is reported. The data for this analysis stem from the municipality of Voorhout in the Netherlands. Data were collected in 1997 and 1998 before and after opening of a new railway station. Results of the analysis indicate that specific household and individual attributes have a larger effect on daily activity patterns than others and that the effect of these attributes has significantly changed. Because changes in other sociodemographic attributes are almost nonexistent and activity patterns for communities are known to be stable, this study claims that the observed shifts in dependencies come from this new station.

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Hudson, Nicky, Caroline Law, Lorraine Culley, Helene Mitchell, Elaine Denny, and Nick Raine-Fenning. "Conducting dyadic, relational research about endometriosis: A reflexive account of methods, ethics and data analysis." Health: An Interdisciplinary Journal for the Social Study of Health, Illness and Medicine 24, no. 1 (July 6, 2018): 79–93. http://dx.doi.org/10.1177/1363459318786539.

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Despite a growing literature on the value of relational data in studies of social phenomena, individuals still commonly constitute the basic unit of analysis in qualitative research. Methodological aspects of interviewing couples, particularly interviewing partners separately, and of conducting dyadic analysis have received scant attention. This article describes the experience of conducting separate interviews with both partners in 22 heterosexual couples (n = 44) in a study of the impact of the gynaecological condition endometriosis. In order to advance current methodological thinking regarding interviewing couples, we describe the dyadic, relational approach employed in designing the study and our specific method of dyadic analysis. We argue that utilising separate interviews with dyadic analysis rather than conducting joint interviews, while not without its ethical, practical and analytical challenges, offers considerable methodological benefits. Such an approach allows a unique relational insight into the impact of chronic illness on couples and how they navigate chronic illness by illuminating both shared and individual interpretations, experiences, understandings and meanings.

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Knies, Gundi. "Effects of Income and Material Deprivation on Children’s Life Satisfaction: Evidence from Longitudinal Data for England (2009–2018)." Journal of Happiness Studies 23, no. 4 (October 5, 2021): 1469–92. http://dx.doi.org/10.1007/s10902-021-00457-3.

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AbstractA plethora of research shows that income is an important factor in adult’s life satisfaction, but research ascertaining its importance for children’s life satisfaction is scant. Using a largescale nationally representative longitudinal survey with children aged 10–15, we estimate comprehensive life satisfaction models that account for heterogeneity in exogenous circumstances in children’s lives, focussing on family income and material deprivation. We find empirical support for the hypothesis that children are more satisfied with their lives, the more income their family has and the less material deprivation they experience throughout their teens. There are, however, differences across age groups with children aged 12–15 experiencing greater life satisfaction losses on account of lower family material wellbeing than younger children. Overall, income effects for older children are small but statistically significant when accounting for unobserved individual differences.

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Coleman, Danielle. "Digital Colonialism: The 21st Century Scramble for Africa through the Extraction and Control of User Data and the Limitations of Data Protection Laws." Michigan Journal of Race & Law, no. 24.2 (2019): 417. http://dx.doi.org/10.36643/mjrl.24.2.digital.

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As Western technology companies increasingly rely on user data globally, extensive data protection laws and regulations emerged to ensure ethical use of that data. These same protections, however, do not exist uniformly in the resource-rich, infrastructure-poor African countries, where Western tech seeks to establish its presence. These conditions provide an ideal landscape for digital colonialism. Digital colonialism refers to a modern-day “Scramble for Africa” where largescale tech companies extract, analyze, and own user data for profit and market influence with nominal benefit to the data source. Under the guise of altruism, large scale tech companies can use their power and resources to access untapped data on the continent. Scant data protection laws and infrastructure ownership by western tech companies open the door for exploitation of data as a resource for-profit and a myriad of uses including predictive analytics. One may believe that strengthening data protection laws will be a barrier to digital colonialism. However, regardless of their relative strength or weakness, data protection laws have limits. An analysis of Kenya's 2018 data protection bill, the General Data Protection Regulation (GDPR), and documented actions of largescale tech companies exemplifies how those limits create several loopholes for continued digital colonialism including, historical violations of data privacy laws; limitations of sanctions; unchecked mass concentration of data, lack of competition enforcement, uninformed consent, and limits to defined nation-state privacy laws.

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Skotarczak, E., K. Molinski, T. Szwaczkowski, and A. Dobek. "Bayesian analysis of ordinal categorical data under a mixed inheritance model." Archives Animal Breeding 54, no. 1 (October 10, 2011): 93–103. http://dx.doi.org/10.5194/aab-54-93-2011.

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Abstract. The effectiveness of proposed Gibbs sampling (GS) algorithm to detect single loci determining livestock threshold traits under a different hypothetical breeding and statistical modeling scenarios was examined. The following factors were included into the analysis: the presence of fixed effects, knowledge of one threshold, the size of the population (1 212 and 3 070 pedigreed individuals, respectively) and proportions of individuals in three genotypic classes. Five threshold and one linear unitrait animal model were employed to analysis of these datasets. The GS algorithm was applied to estimate fixed effects (optionally), additive polygenic variance, single allele frequencies, genotypic effects and one threshold (optionally). For each case, 2 000 000 rounds of GS were conducted. The first 1 000 000 steps were discarded as a burn-in-period. The results were collected from every 20th iteration. In general, the accuracy of parameter estimates is not satisfactory. However, taking into account the scant amount of information provided by the ordinal categorical data, it seems that such an analysis is a good first approach. Except for one case in which the estimate was very close to the true value, in all the other cases the estimated gene effect was smaller than the true effect. In general, the algorithm proposed does not provide overestimated effects of single locus.

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Hogg, Carolyn J., Luke Silver, Elspeth A. McLennan, and Katherine Belov. "Koala Genome Survey: An Open Data Resource to Improve Conservation Planning." Genes 14, no. 3 (February 22, 2023): 546. http://dx.doi.org/10.3390/genes14030546.

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Genome sequencing is a powerful tool that can inform the management of threatened species. Koalas (Phascolarctos cinereus) are a globally recognized species that captured the hearts and minds of the world during the 2019/2020 Australian megafires. In 2022, koalas were listed as ‘Endangered’ in Queensland, New South Wales, and the Australian Capital Territory. Populations have declined because of various threats such as land clearing, habitat fragmentation, and disease, all of which are exacerbated by climate change. Here, we present the Koala Genome Survey, an open data resource that was developed after the Australian megafires. A systematic review conducted in 2020 demonstrated that our understanding of genomic diversity within koala populations was scant, with only a handful of SNP studies conducted. Interrogating data showed that only 6 of 49 New South Wales areas of regional koala significance had meaningful genome-wide data, with only 7 locations in Queensland with SNP data and 4 locations in Victoria. In 2021, we launched the Koala Genome Survey to generate resequenced genomes across the Australian east coast. We have publicly released 430 koala genomes (average coverage: 32.25X, range: 11.3–66.8X) on the Amazon Web Services Open Data platform to accelerate research that can inform current and future conservation planning.

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Raudies, Florian, and Rick O. Gilmore. "Visual Motion Priors Differ for Infants and Mothers." Neural Computation 26, no. 11 (November 2014): 2652–68. http://dx.doi.org/10.1162/neco_a_00645.

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Visual motion direction ambiguities due to edge-aperture interaction might be resolved by speed priors, but scant empirical data support this hypothesis. We measured optic flow and gaze positions of walking mothers and the infants they carried. Empirically derived motion priors for infants are vertically elongated and shifted upward relative to mothers. Skewed normal distributions fitted to estimated retinal speeds peak at values above 20[Formula: see text]/sec.

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Hoseini, Seyyed Mohammad Sadat. "Comparison of Microscopic Drivers' Probabilistic Lane-changing Models With Real Traffic Microscopic Data." PROMET - Traffic&Transportation 23, no. 4 (January 25, 2012): 241–51. http://dx.doi.org/10.7307/ptt.v23i4.127.

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The difficulties of microscopic-level simulation models to accurately reproduce real traffic phenomena stem not only from the complexity of calibration and validation operations, but also from the structural inadequacies of the sub-models themselves. Both of these drawbacks originate from the scant information available on real phenomena because of the difficulty in gathering accurate field data. This paper studies the traffic behaviour of individual drivers utilizing vehicle trajectory data extracted from digital images collected from freeways in Iran. These data are used to evaluate the four proposed microscopic traffic models. One of the models is based on the traffic regulations in Iran and the three others are probabilistic models that use a decision factor for calculating the probability of choosing a position on the freeway by a driver. The decision factors for three probabilistic models are increasing speed, decreasing risk of collision, and increasing speed combined with decreasing risk of collision. The models are simulated by a cellular automata simulator and compared with the real data. It is shown that the model based on driving regulations is not valid, but that other models appear useful for predicting the driver’s behaviour on freeway segments in Iran during noncongested conditions.

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Howe, Nicola, Emma Giles, Dorothy Newbury-Birch, and Elaine McColl. "Systematic review of participants’ attitudes towards data sharing: a thematic synthesis." Journal of Health Services Research & Policy 23, no. 2 (April 2018): 123–33. http://dx.doi.org/10.1177/1355819617751555.

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Objectives Data sharing is well established in biological research, but evidence on sharing of clinical trial or public health research study data remains limited, in particular studies of research participants’ perspectives of data sharing. This study systematically reviewed international evidence of research participants’ attitudes towards the sharing of data for secondary research use. Methods Systematic search of seven databases, and author-, citation- and bibliography-follow up to identify studies examining research participants’ attitudes towards data sharing. Studies were thematically analysed using NVivo v10 to identify recurring themes. Results Nine studies were eligible for inclusion. Thematic analysis identified four key themes: (1) benefits of data sharing, including benefit to participants or immediate community, benefits to the public and benefits to science or research; (2) fears and harms, such as fear of exploitation, stigmatization or repercussions, alongside concerns about confidentiality and misuse of data; (3) data sharing processes, in particular the role of consent in the process; and (4) the relationship between participants and research such as trust in different types of research or organization and the relationship with the original research team. Conclusions The available literature on attitudes towards sharing data from clinical trials or public health interventions remains scant. This study has identified four themes regarding research participants’ attitudes and preferences, which should be considered by policy makers, and explored with further research.

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Xu, Wen, and Katina Zammit. "Applying Thematic Analysis to Education: A Hybrid Approach to Interpreting Data in Practitioner Research." International Journal of Qualitative Methods 19 (January 1, 2020): 160940692091881. http://dx.doi.org/10.1177/1609406920918810.

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Thematic analysis (TA), as a qualitative analytic method, is widely used in health care, psychology, and beyond. However, scant details are often given to demonstrate the process of data analysis, especially in the field of education. This article describes how a hybrid approach of TA was applied to interpret multiple data sources in a practitioner inquiry. Particular attention is given to the inductive and deductive coding and theme development process of TA. Underpinned by the constructivist epistemology, codes were driven by both data per se and theories, through a “bottom-up” and “top-down” approach to identify themes. A detailed example of six steps of data analysis is presented, which evidences the systematic analysis of raw data from observation and research journals, students’ focus groups, and a classroom teacher’s semistructured interviews. This example demonstrates how classroom practice was unpacked and how insiders’ insights were interpreted through the theoretical lens while also allowing the participants to express themselves. By providing step-by-step guidelines in data coding and identification of themes, this article contributes to informing qualitative researchers, especially teacher-researchers who undertake their research in the classroom setting.

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Anderson, Theresa, Randy D. Colón, Abigail Goben, and Sebastian Karcher. "Curating for Accessibility." International Journal of Digital Curation 17, no. 1 (August 3, 2022): 10. http://dx.doi.org/10.2218/ijdc.v17i1.837.

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Accessibility of research data to disabled users has received scant attention in literature and practice. In this paper we briefly survey the current state of accessibility for research data and suggest some first steps that repositories should take to make their holdings more accessible. We then describe in depth how those steps were implemented at the Qualitative Data Repository (QDR), a domain repository for qualitative social-science data. The paper discusses accessibility testing and improvements on the repository and its underlying software, changes to the curation process to improve accessibility, as well as efforts to retroactively improve the accessibility of existing collections. We conclude by describing key lessons learned during this process as well as next steps.

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van de Maat, Robin, Johan Lataster, and Peter Verboon. "Why and How to Deal With Diurnal Cyclic Patterns in Ambulatory Assessment of Emotions." European Journal of Psychological Assessment 36, no. 3 (May 2020): 471–81. http://dx.doi.org/10.1027/1015-5759/a000579.

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Abstract. The use of ambulatory assessment (AA) based methods in emotion research has steadily increased over the past decades. Although having a number of benefits over other methods, the use and analysis of AA data may pose specific challenges. Among these, the issue of dealing with diurnal cycles in emotion data has received relative scant attention. This article therefore discusses why cyclic models may be considered for analyzing AA data on emotions, and describes how this approach can be applied to an empirical AA dataset. Results suggest that cyclic modeling may be a useful method for describing and accounting for (diurnal) cyclic patterns in AA data, but should be used with a number of considerations in mind.

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E., Chinomona, and Sandada M. . "An Investigation of Shared Value, Benefit, Commitment, Trust and Retention in the Banking Sector: A Student Perspective." Journal of Economics and Behavioral Studies 6, no. 8 (August 30, 2014): 607–15. http://dx.doi.org/10.22610/jebs.v6i8.521.

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Despite the increase in research focusing on service relationship level in the banking sector, research on relationship benefit, student perceived shared value on relationship commitment, trust and student retention in the African banking context is still scant. Therefore, using a data set of 175 from students in colleges and universities in Johannesburg, this study examines these relationships. Smart PLS software technique was used to statistically analyse the measurement and structural models. All the posited six hypotheses were supported. The findings from the data analysis proved that there is a strong positive relationship between all six hypotheses.

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Gatto, Marcel, and Abu Hayat Md Saiful Islam. "Impacts of COVID-19 on rural livelihoods in Bangladesh: Evidence using panel data." PLOS ONE 16, no. 11 (November 29, 2021): e0259264. http://dx.doi.org/10.1371/journal.pone.0259264.

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Rapid assessments have been emerging on the effects of COVID-19, yet rigorous analyses remain scant. Here, rigorous evidence of the impacts of COVID-19 on several livelihood outcomes are presented, with a particular focus on heterogenous effects of COVID-19. We use a household-level panel dataset consisting of 880 data points collected in rural Bangladesh in 2018 and 2020, and employ difference-in-differences with fixed effects regression techniques. Results suggest that COVID-19 had significant and heterogenous effects on livelihood outcomes. Agricultural production and share of production sold were reduced, especially for rice crops. Further, diet diversity and education expenditure were reduced for the total sample. Households primarily affected by (fear of) sickness had a significantly lower agricultural production, share of crop market sales, and lower health and education expenditure, compared to households affected by other COVID-19 effects, such as travel restrictions. In turn, (fear of) sickness and the correlated reduced incidence of leaving the house, resulted in higher off-farm incomes suggesting that households engage in less physically demanding and localized work. Policy-makers need to be cognizant of these heterogenous COVID-19 effects and formulate policies that are targeted at those households that are most vulnerable (e.g., unable/willing to leave the house due to (fear of) sickness).

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Montagna, Francesca, Giulia Marcocchia, and Marco Cantamessa. "Tackling the Design of Platform-Based Service Systems, Integrating Data and Cultures: The Case of Urban Markets." Systems 11, no. 2 (January 28, 2023): 66. http://dx.doi.org/10.3390/systems11020066.

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Different design traditions address the design of services. When adopted alone, they can limit design, especially if services systems are complex. Some combinations among service design traditions are theorized in the literature and a cultural synthesis is considered a priority. This paper discusses a practical application of that synthesis: systematic/data-driven methods from engineering and service innovation are applied within a participatory and transformative environment. Intangible versus material and functional versus experience service elements are considered. The case study on urban markets shows that economics and the transactional/functional mechanics of a service system must be understood for proper design actions, and that overcoming separations between strands of literature is necessary to achieve this aim. Moreover, since urban markets are two-sided platforms in a physical setting, the study allows easier investigation than in modern digital platforms regarding how platform economics affect the design of a service system, providing insights for digital services as well. Originality is due to generally scant contributions on urban market design, since markets are often regulated, rather than designed, beyond the rare practical attempts of cultural synthesis.

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Suman, Anna Berti, Sven Schade, and Yasuhito Abe. "Exploring legitimization strategies for contested uses of citizen-generated data for policy." Journal of Human Rights and the Environment 11, no. 3 (December 25, 2020): 74–102. http://dx.doi.org/10.4337/jhre.2020.03.04.

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In this article, we investigate how citizens use data they gather as a rhetorical resource for demanding environmental policy interventions and advancing environmental justice claims. While producing citizen-generated data (CGD) can be regarded as a form of ‘social protest’, citizens and interested institutional actors still have to ‘justify’ the role of lay people in producing data on environmental issues. Such actors adopt a variety of arguments to persuade public authorities to recognize CGD as a legitimate resource for policy making and regulation. So far, scant attention has been devoted to inspecting the different legitimization strategies adopted to push for institutional use of CGD. In order to fill this knowledge gap, we examine which distinctive strategies are adopted by interested actors: existing legitimization arguments are clustered, and strategies are outlined, based on a literature review and exemplary cases. We explore the conceivable effects of these strategies on targeted policy uses. Two threads emerge from the research, entailing two complementary arguments: namely that listening to CGD is a governmental obligation and that including CGD is ultimately beneficial for making environmental decisions. We conclude that the most used strategies include showing the scientific strength and contributory potential of CGD, whereas environmental rights and democracy-based strategies are still rare. We discuss why we consider this result to be problematic and outline a future research agenda.

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Journal articles on the topic 'Scant data'

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