scholarly journals Citizen Social Scientists’ Observations on Complex Tasks Match Trained Research Assistants’, Suggesting Lived Experiences are Valuable in Data Collection

2021 ◽  
Vol 6 (1) ◽  
pp. 37
Author(s):  
Cindi SturtzSreetharan ◽  
Alissa Ruth ◽  
Amber Wutich ◽  
Meskerem Glegziabher ◽  
Charlayne Mitchell ◽  
...  
Keyword(s):  
Data Collection ◽  
Lived Experiences ◽  
Social Scientists ◽  
Complex Tasks ◽  
Research Assistants

scholarly journals Freedom of Information (FOI) as a data collection tool for social scientists

PLoS ONE ◽  
2020 ◽  
Vol 15 (2) ◽  
pp. e0228392
Author(s):  
Joanna Clifton-Sprigg ◽  
Jonathan James ◽  
Sunčica Vujić
Keyword(s):  
Data Collection ◽  
Freedom Of Information ◽  
Data Collection Tool ◽  
Social Scientists

scholarly journals From a Smoking Gun to Spent Fuel: Principled Subsampling Methods for Building Big Language Data Corpora from Monitor Corpora

Data ◽  
2019 ◽  
Vol 4 (2) ◽  
pp. 48 ◽  
Author(s):  
Jacqueline Tidwell
Keyword(s):  
Data Collection ◽  
Sampling Method ◽  
Evaluation Process ◽  
Spent Fuel ◽  
Social Scientists ◽  
Multiple Sampling ◽  
Language Data ◽  
Representative Model ◽  
Data Culture ◽  
Final Text

With the influence of Big Data culture on qualitative data collection, acquisition, and processing, it is becoming increasingly important that social scientists understand the complexity underlying data collection and the resulting models and analyses. Systematic approaches for creating computationally tractable models need to be employed in order to create representative, specialized reference corpora subsampled from Big Language Data sources. Even more importantly, any such method must be tested and vetted for its reproducibility and consistency in generating a representative model of a particular population in question. This article considers and tests one such method for Big Language Data downsampling of digitally accessible language data to determine both how to operationalize this form of corpus model creation, as well as testing whether the method is reproducible. Using the U.S. Nuclear Regulatory Commission’s public documentation database as a test source, the sampling method’s procedure was evaluated to assess variation in the rate of which documents were deemed fit for inclusion or exclusion from the corpus across four iterations. After performing multiple sampling iterations, the approach pioneered by the Tobacco Documents Corpus creators was deemed to be reproducible and valid using a two-proportion z-test at a 99% confidence interval at each stage of the evaluation process–leading to a final mean rejection ratio of 23.5875 and variance of 0.891 for the documents sampled and evaluated for inclusion into the final text-based model. The findings of this study indicate that such a principled sampling method is viable, thus necessitating the need for an approach for creating language-based models that account for extralinguistic factors and linguistic characteristics of documents.

scholarly journals Evaluating Closures of Fresh Fruit and Vegetable Vendors During the COVID-19 Pandemic: Methodology and Preliminary Results Using Omnidirectional Street View Imagery

10.2196/23870 ◽  
2021 ◽  
Vol 5 (2) ◽  
pp. e23870
Author(s):  
Shahmir H Ali ◽  
Valerie M Imbruce ◽  
Rienna G Russo ◽  
Samuel Kaplan ◽  
Kaye Stevenson ◽  
...  
Keyword(s):  
Data Collection ◽  
Fresh Fruit ◽  
Surveillance Data ◽  
Fruit And Vegetable ◽  
Google Maps ◽  
Retail Environment ◽  
Google Street View ◽  
Street View ◽  
Research Assistants ◽  
Imagery Data

Background The COVID-19 pandemic has significantly disrupted the food retail environment. However, its impact on fresh fruit and vegetable vendors remains unclear; these are often smaller, more community centered, and may lack the financial infrastructure to withstand supply and demand changes induced by such crises. Objective This study documents the methodology used to assess fresh fruit and vegetable vendor closures in New York City (NYC) following the start of the COVID-19 pandemic by using Google Street View, the new Apple Look Around database, and in-person checks. Methods In total, 6 NYC neighborhoods (in Manhattan and Brooklyn) were selected for analysis; these included two socioeconomically advantaged neighborhoods (Upper East Side, Park Slope), two socioeconomically disadvantaged neighborhoods (East Harlem, Brownsville), and two Chinese ethnic neighborhoods (Chinatown, Sunset Park). For each neighborhood, Google Street View was used to virtually walk down each street and identify vendors (stores, storefronts, street vendors, or wholesalers) that were open and active in 2019 (ie, both produce and vendor personnel were present at a location). Past vendor surveillance (when available) was used to guide these virtual walks. Each identified vendor was geotagged as a Google Maps pinpoint that research assistants then physically visited. Using the “notes” feature of Google Maps as a data collection tool, notes were made on which of three categories best described each vendor: (1) open, (2) open with a more limited setup (eg, certain sections of the vendor unit that were open and active in 2019 were missing or closed during in-person checks), or (3) closed/absent. Results Of the 135 open vendors identified in 2019 imagery data, 35% (n=47) were absent/closed and 10% (n=13) were open with more limited setups following the beginning of the COVID-19 pandemic. When comparing boroughs, 35% (28/80) of vendors in Manhattan were absent/closed, as were 35% (19/55) of vendors in Brooklyn. Although Google Street View was able to provide 2019 street view imagery data for most neighborhoods, Apple Look Around was required for 2019 imagery data for some areas of Park Slope. Past surveillance data helped to identify 3 additional established vendors in Chinatown that had been missed in street view imagery. The Google Maps “notes” feature was used by multiple research assistants simultaneously to rapidly collect observational data on mobile devices. Conclusions The methodology employed enabled the identification of closures in the fresh fruit and vegetable retail environment and can be used to assess closures in other contexts. The use of past baseline surveillance data to aid vendor identification was valuable for identifying vendors that may have been absent or visually obstructed in the street view imagery data. Data collection using Google Maps likewise has the potential to enhance the efficiency of fieldwork in future studies.

The Lived Experiences of SEAMEO INNOTECH GURO21 Graduates

2020 ◽  
Vol 2 (2) ◽  
pp. 91-120
Author(s):  
JOJIE RUPINTA HONCULADA
Keyword(s):  
Data Collection ◽  
Teacher Development ◽  
21St Century ◽  
Lived Experiences ◽  
Online Courses ◽  
Primary Data ◽  
Online Course ◽  
Development Programs ◽  
Collection Method ◽  
School Heads

This study examines the experiences of eight teachers who have graduated from an online course. The SEAMEO INNOTECH GURO21. The primary data collection method made use of one on one interviews.  The results of the study informed that in understanding the lived experiences of those who graduated from the first course of SEAMEO INNOTECH GURO21 can be categorized into two themes: (a) equipping teachers with the knowledge, skills, attitudes and values of the 21st century; and (2) facilitating 21st century learning. This research revealed that as teachers, one must be knowledgeable enough to carefully choose strategies and techniques tailored-fit for the kind and level of the learners. The acquisition of the 21st century skills has become an essential part of the generation. Thus, teachers must undergo seminars and workshops and even enroll in online courses to be upgraded with the latest trends of this generation. The participants, from their responses, revealed the change within themselves in line with their profession and in the development of their personality. The course had made them shift from being a traditional teacher to a techno-savvy one. This means using techniques and strategies the old way and how they smoothly transformed into technology-based teaching. Recommendations are offered for school heads, and for further research. This is to further enhance this study and to compare other findings in line with teacher development programs through online courses.

Journaling among home care workers during the COVID-19 pandemic: A promising method for qualitative data collection

2021 ◽  
pp. 147332502110648
Author(s):  
Julia I Bandini ◽  
Julia Rollison ◽  
Jason Etchegaray
Keyword(s):  
Public Health ◽  
Data Collection ◽  
Home Care ◽  
Lived Experiences ◽  
Health Agency ◽  
The United States ◽  
Lessons Learned ◽  
Future Research ◽  
Care Workers ◽  
Home Care Workers

Qualitative methods that capture individual lived experiences throughout rapidly changing circumstances are particularly important during public health emergencies. The COVID-19 pandemic has put home care workers at risk as they provide vital services in homes to individuals with chronic conditions or disabilities. Using a 6-week journaling process in which we enrolled participants at different points, we sought to examine experiences of home care workers ( n = 47) in the United States in New York and Michigan during April–July 2020 of the COVID-19 pandemic. Our methods for data collection and analysis were guided by a general qualitative approach as we aimed to examine the weekly perspectives and lived experiences of home care workers. We asked individuals to respond to our journaling prompts weekly to capture their reflections in “real time.” To better understand home care workers’ perspectives on journaling and the broader external context in which they provided care, we triangulated our data with interviews with home care workers ( n = 19) and home health agency representatives ( n = 9). We explored the feasibility of a rolling journaling process during an unprecedented public health emergency, characterized by rapid changes and uncertainty in day-to-day life, and reflect on lessons learned to guide future research on journaling for data collection, particularly for marginalized workers during public health crises, when events are evolving rapidly.

Consent and Assent to Participate in Research from People with Dementia

2007 ◽  
Vol 14 (1) ◽  
pp. 27-40 ◽  
Author(s):  
Susan Slaughter ◽  
Dixie Cole ◽  
Eileen Jennings ◽  
Marlene A Reimer
Keyword(s):  
Informed Consent ◽  
Data Collection ◽  
Vulnerable Populations ◽  
Research Participation ◽  
Minimal Risk ◽  
Careful Attention ◽  
People With Dementia ◽  
Practical Guidelines ◽  
Conducting Research ◽  
Research Assistants

Conducting research with vulnerable populations involves careful attention to the interests of individuals. Although it is generally understood that informed consent is a necessary prerequisite to research participation, it is less clear how to proceed when potential research participants lack the capacity to provide this informed consent. The rationale for assessing the assent or dissent of vulnerable individuals and obtaining informed consent by authorized representatives is discussed. Practical guidelines for recruitment of and data collection from people in the middle or late stage of dementia are proposed. These guidelines were used by research assistants in a minimal risk study.

scholarly journals The Ethnomathematics Practices of Eskaya Tribe

2021 ◽  
Vol 12 (3) ◽  
pp. 3767-3777
Author(s):  
Fe R. Janiola Et.al
Keyword(s):  
Data Collection ◽  
Research Design ◽  
Lived Experiences ◽  
Daily Life ◽  
Study Data ◽  
Measuring Time ◽  
Mathematical Practices ◽  
Key Informants ◽  
Purposive Sampling ◽  
Numeration Systems

This research sought to describe the Ethno-mathematical practices of the Eskaya tribe of Taytay, Duero, Bohol using the ethnographical research design to explore the ethnomathematics practices through the lived experiences of the informants. Employing purposive sampling, selected teachers, parents, and students from the tribe served as the key informants of the study. Data collection took almost a year of observation, lived experiences documentation, and interviews. The study was able to describe some of the ethnomathematical practices of the Eskaya tribe such as the skills and processes of the Eskaya tribe commonly use in their daily life in counting, measuring, ciphering, ordering, classifying, inferring, and modeling patterns. These skills and techniques were used in studying their Eskaya numeration systems such as the Eskaya numbers and numerals, the Eskaya name of the basic shapes and the four fundamental operations, and the use of Eskaya numbers in measuring time, days, and months.

scholarly journals Observing Materiality in Organizations

M n gement ◽  
2020 ◽  
Vol 23 (3) ◽  
pp. 9-27
Author(s):  
Isabelle Royer
Keyword(s):  
Decision Making ◽  
Data Collection ◽  
Physical Environment ◽  
Lived Experiences ◽  
Final Section ◽  
Organizational Research ◽  
The Past ◽  
Physical Environments ◽  
Definition Of ◽  
Three Components

Research on materiality has grown rapidly over the past 10 years, highlighting the influence of physical artifacts and spaces in organizations, which had been overshadowed by discursive approaches. This body of research enriches our understanding of organizations in many areas including technology, decision-making, routines, learning, identity, culture, power, and institutions. However, researchers sometimes struggle to select methods suited to study materiality, as previous works have not been explicit in that respect. This article calls organizational researchers interested in physical environments – that is, artifacts and spaces – to integrate observation into their data collection. The first section presents a tripartite definition of the physical environment including activities, conceptions, and lived experiences. Ontological debates are introduced, and observation is proposed as a relevant method for studying materiality in organizational research. The second section presents observation techniques based on three approaches: observing materiality in actions, observing beyond seeing, and making participants observe. Each approach is mainly associated with one of the three components of materiality. The final section discusses the scope of observation techniques, suggests how to combine approaches, and flags difficulties associated with visual techniques.

scholarly journals Research assistants’ perception of mistreatment and the strategies they prefer to overcome this mistreatment

2015 ◽  
Vol 12 (2) ◽  
pp. 1662
Author(s):  
Gizem Günçavdı ◽  
Soner Polat
Keyword(s):  
Data Collection ◽  
Faculty Members ◽  
Organizational Variables ◽  
Significant Difference ◽  
The Future ◽  
Secondary Appraisal ◽  
Descriptive Survey ◽  
Research Assistants

<p>The purpose of this study is to determine research assistants’ perception of mistreatment from other faculty members and the strategies they prefer to overcome this mistreatment. The sample of this study includes 255 research assistants who work at seven faculties at Kocaeli University, Turkey. This study is in the descriptive survey model. In order to measure research assistants’ perception of mistreatment, “Mistreatment Scale” developed by Harlos and Axelrod (2005) and adapted to Turkish by Günçavdı and Polat (2015); and in order to measure strategies which research assistants prefer to overcome this mistreatment, “Secondary Appraisal Scale” developed by Rogers (1998) were used as data collection tools. It has been found out that research assistants’ perception of mistreatment from faculty showed significant difference depending on personal and organizational variables.  Also it has been found out that research assistants used “barriers” strategies mostly to overcome mistreatment. This research has given an idea about research assistants’ experiences about being exposed to mistreatment, but this study is limited to students at Kocaeli University. In the future researches, the samples can be extended by taking research assistants who work at other universities as the sample.  </p>

scholarly journals On the Same Page: A Formal Process for Training Multiple Interviewers

2018 ◽  
Author(s):  
Carolyn Sattin-Bajaj
Keyword(s):  
Data Collection ◽  
Training Program ◽  
Qualitative Data ◽  
Social Science Research ◽  
Science Research ◽  
Training Models ◽  
Multi Stage ◽  
Data Collection And Analysis ◽  
Qualitative Methodologies ◽  
Research Assistants

The increased utilization of qualitative methodologies as part of mixed-method health and social science research has highlighted the need for training procedures for every stage of qualitative data collection and analysis. Yet, few group training models exist for collecting reliable, valid qualitative interview data. This article presents a multi-stage, collaborative interview training process for a large team of research assistants. The training program combines insights and techniques used in both structured and semi-structured interviewing. It also includes ongoing instruction and feedback prior to and during data collection in an effort to ensure consistency and reliability. In the article, I describe each stage of the training program in detail, review some of the challenges encountered during implementation, and conclude with a discussion of how researchers and course instructors might adapt the methods to fit their particular needs.

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