Womanism and Snowball Sampling: Engaging Marginalized Populations in Holistic Research
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Womanist and feminist qualitative researchers continue to identify research methods and techniques that harness the power of social networking and personal connections while engaging with marginalized populations. Many have found that the use of snowball sampling allows increased access to individuals and groups that may otherwise remain inaccessible. The purpose of this article is to discuss the use of snowball sampling techniques within womanist and feminist research. The authors offer critical reflections of the use of this sampling technique as a tool that allows researchers access to “hidden” and marginalized populations. An example of the use of snowball sampling in a doctoral research project, which looks at the experiences of Black women faculty in New Mexico’s institutions of higher education, is provided. The article concludes with recommended strategies and key considerations about the use of snowball sampling in womanist research.Keywords:
Snowball sampling
Using data from an enumerated network of worldwide flight connections between airports, we examine how sampling designs and sample size influence network metrics. Specifically, we apply three types of sampling designs: simple random sampling, nonrandom strategic sampling (i.e., selection of the largest airports), and a variation of snowball sampling. For the latter sampling method, we design what we refer to as a controlled snowball sampling design, which selects nodes in a manner analogous to a respondent-driven sampling design. For each design, we evaluate five commonly used measures of network structure and examine the percentage of total air traffic accounted for by each design. The empirical application shows that (1) the random and controlled snowball sampling designs give rise to more efficient estimates of the true underlying structure, and (2) the strategic sampling method can account for a greater proportion of the total number of passenger movements occurring in the network.
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Respondent driven sampling as a chain referral approach has been utilized for finding a sample of people from a hidden or a hard to reach population by following social links from sample individuals to detect additional members of the target population to form final sample. This sampling method has been applied successfully in several countries for sampling in networks such as injecting drug users, female sex workers, men who have sex with men and immigrants. The aim of this article is to explore the problems involved in conducting research with hidden populations and to suggest two chain referral strategies to recruit sample participants. Finally, the merit of respondent driven sampling comparing to the most applicable chain referral sampling method, snowball sampling, is discussed.Keywords: Chain Referral Sampling, Conventional Sampling, Hard to Reach Population, Respondent Driven Sampling, Snowball Sampling
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Survey Sampling
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Respondent-driven sampling is a network sampling technique typically employed for hard-to-reach populations (for example, drug users, men who have sex with men, people with HIV). Similarly to snowball sampling, initial seed respondents recruit additional respondents from their network of friends. The recruiting process repeats iteratively, thereby forming long referral chains. Unlike in snowball sampling, it is crucial to obtain estimates of respondents’ personal network sizes (that is, number of acquaintances in the target population) and information about who recruited whom. Markov chain theory makes it possible to derive population estimates and sampling weights. We introduce a new Stata command for respondent-driven sampling and illustrate its use.
Snowball sampling
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Қaй уaқыттa болмaсын мәдениетaрaлық қaрым-қaтынaстaрдың жaқсы деңгейде жүзеге aсуы не құлдырaуы бaстaпқы мәтіннің бaсқa тілдегі aудaрмaсымен aдеквaтты не бaлaмaлы болуынa тікелей бaйлaнысты. Осығaн орaй, көптеген ғaлымдaр aдеквaттылық пен бaлaмaлылық терминдерін зерттеуге жітінaзaр aудaрудa. Сондықтaн осы тaқырыпты зерттейтін теориялaрдың сaны күн-нен күнге aртып келеді. Кей ғaлымдaрдың есептеуінше, aдеквaттық және бaлaмaлық ұғымдaры бір мaғынaны білдіреді, aл бaсқaлaры олaрдың ұқсaстықтaры көп болғaнымен оны екі бөлек ұғым ретінде қaрaстыру керек деп пaйымдaйды. Сол себептібұл жұмыстың мaқсaты – aдеквaттылық және бaлaмaлылық ұғымдaрыныңмәнің aдевaтты және бaлaмa aудaрмaлaры турaлы теориялaрды жүйелеу және топтaстырып, сaрaлaу aрқылы aжырaту. Бір жaғынaн, бұл оқырмaнғa удaрмaтaнымындaғы aдеквaттылық және бaлaмaлық ұғымдaрын оңaй түсінуге,екінші жaғынaн бұл бізге екі ұғымның aйырмa шылықтaры мен ұқсaстықтaрынaнықтaуғa мүмкіндік береді. Зерттеу мaқсaтын жүзеге aсыру үшін жұмысбaрысындa сaлыстырмaлытaлдaу әдісі қолдaнылды. Шетелдік ғaлымдaрдың зерттеулерінің негізінде бұл жұмыстa aдеквaтты және бaлaмaлы aудaрм aның ұқсaс тұстaры мен aйырмaшылықтaры тaлдaнды. Тaлдaуғa сәйкес біз aдеквaтты aудaрмa ретінде күтілетін коммуникaтивтік әсерді қaмтaмaсыз етеді, сондaй-aқ оның бaсты тaлaптaрының бірі түпнұсқaның мaғынaсын толықтaй жеткізу үшін бaлaмaлaрды қолдaну деп қaрaстырaмыз. Бірaқ бaлaмaлы aудaрмa өз тaрaпындa прaгмaтикaлық мaқсaтты әрдaйым қaмтaмaсыз ете aлмaйды, әрі әрқaшaн aудaрмaның конвенционaлды нормaтивті тaлaптaрынa сәкес болa бермейді.
Socialization
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Respondent driven sampling (RDS) is a network sampling technique typically employed for hard-to-reach populations (e.g. drug users, men who have sex with men, people with HIV). Similar to snowball sampling, initial seed respondents recruit additional respondents from their network of friends. The recruiting process repeats iteratively, thereby forming long referral chains. Unlike in snowball sampling, it is crucial to obtain estimates of respondents' personal network size (i.e., number of acquaintances in the target population) and information about who recruited whom. Markov chain theory makes it possible to derive population estimates and sampling weights. We introduce a new Stata program for RDS and illustrate its use.
Snowball sampling
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Respondent-driven sampling is a network sampling technique typically employed for hard-to-reach populations (for example, drug users, men who have sex with men, people with HIV). Similarly to snowball sampling, initial seed respondents recruit additional respondents from their network of friends. The recruiting process repeats iteratively, thereby forming long referral chains. Unlike in snowball sampling, it is crucial to obtain estimates of respondents' personal network sizes (that is, number of acquaintances in the target population) and information about who recruited whom. Markov chain theory makes it possible to derive population estimates and sampling weights. We introduce a new Stata command for respondent-driven sampling and illustrate its use.
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Survey Sampling
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The principal objective of this study was to profile qualitative research in social sciences through a comprehensive examination of 10,637 documents. An analysis on how scholars from central/peripheral countries included in the qualitative research citations/publications is presented. Central/peripheral distinction is used to determine the trends in the globalization of qualitative research. With the comprehensive examination, this paper will shed light on the discussion of the patterns of globalization in qualitative research. Science mapping technique among bibliometric methods was employed. This paper is based on studies that published in journals that use the English word/term "qualitative" in their titles. The data for this study encompassed 10,637 documents published between 1995 and 2019 by 16,884 authors. Our findings reveal that qualitative research continue to be mostly North America- and Europe-centered initiatives. A similar situation is also observed for the most cited publications and the affiliated institutes of their authors. The studies focus primarily on the individuals' self and social experiences, social psychology, and their knowledge, attitude, and behaviors in education. The most cited publications and the institutions with the highest number of publications are all North America- and Europe-centered. Another finding is that six of every 10 qualitative research are about medical sciences.
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