Abstract
This chapter takes the reader through discussions of three quantitative methodologies that upend traditional positivist-type underpinnings of quantitative inquiry, allowing them to inform inquiry without occluding social factors or dismissing lived experiences, two aspects that are particularly valued under a social model of global public health. First, statistics for marginalized groups is a pragmatic, justice-centered methodology that emphasizes the use of statistics to improve lives. The discussion of this methodology focuses on Indigenous statistics and queer data in particular and makes comparisons with social epidemiology. Second, statistics under a qualitative mental model is a way of statistical thinking that does not distinguish between data as numbers and data as words. This mode of inquiry is demonstrated in its capacity to address inferential questions. Third, diffractive methodology is motivated by new materialist philosophies and emphasizes reading varied forms of data through each other. A focus of this discussion is the relevance of quantitative methodology to such diffractive reading.
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References
Alaimo S (2008) Trans-corporeal feminisms and the ethical space of nature. In: Alaimo S, Hekman S (eds) Material feminisms. Indiana University Press, Bloomington, pp 237–264
Alaimo S (2010) Bodily natures: science, environment, and the material self. Indiana University Press, Bloomington
Barad K (2007) Meeting the universe halfway: quantum physics and the entanglement of matter and meaning. Duke University Press, Durham
Barnes HM (2000) Kaupapa maori: explaining the ordinary. Pac Health Dialog 7(1):13–16
Bauer GR (2014) Incorporating intersectionality theory into population health research methodology: challenges and the potential to advance health equity. Soc Sci Med 110:10–17. https://doi.org/10.1016/j.socscimed.2014.03.022
Benjamin R (2016) Informed refusal: toward a justice-based bioethics. Sci Technol Hum Values 41(6):967–990. https://doi.org/10.1177/0162243916656059
Benjamin R (2019) Race after technology: abolitionist tools for the new Jim Code. Polity Books, Medford
Bourdieu P (1984) Distinction: a social critique of the judgement of taste. Harvard University Press, Cambridge, MA
Bowleg L (2008) When black + lesbian + woman ≠ black lesbian woman: the methodological challenges of qualitative and quantitative intersectionality research. Sex Roles 59:312–325. https://doi.org/10.1007/s11199-008-9400-z
Bowleg L (2012) The problem with the phrase women and minorities: intersectionality–an important theoretical framework for public health. Am J Public Health 102:1267–1273. https://doi.org/10.2105/AJPH.2012.300750
Bryman A (2007) Barriers to integrating quantitative and qualitative research. J Mixed Methods Res 1(1):8–22. https://doi.org/10.1177/2345678906290531
Butler J (1993) Bodies that matter: on the discursive limits of “sex”. Routledge, New York
Chang T, DeJonckheere M, Vinod Vydiswaran VG, Li J, Buis LR, Guetterman TC (2021) Accelerating mixed methods research with natural language processing of big text data. J Mixed Methods Res 15(3):398–412. https://doi.org/10.1177/15586898211021196
Charlton JI (2000) Nothing about us without us: disability oppression and empowerment. University of California Press, Berkeley
Chatterjee P (1994) The nation and its fragments: colonial and postcolonial histories. Princeton University Press, Princeton
Cherryholmes CH (1999) Reading pragmatism. Teachers College Press, New York
Creamer EG (2017) An introduction to fully integrated mixed methods research. Sage, Thousand Oaks
Creswell JW (2014) Research design: qualitative, quantitative, and mixed methods approaches, 4th edn. Sage, London
D’Ignazio C, Klein LF (2020) Data feminism, Kindle edn. MIT Press, Cambridge, MA. Retrieved from Amazon.com
Deleuze G, Guattari F (1987) A thousand plateaus: capitalism and schizophrenia. University of Minnesota Press, Minneapolis
Denzin NK (2009) The elephant in the living room: or extending the conversation about the politics of evidence. Qual Res 9(2):139–160. https://doi.org/10.1177/1468794108098034
Denzin NK (2010) Moments, mixed methods, and paradigm dialogs. Qual Inq 16(6):419–427. https://doi.org/10.1177/1077800410364608
Denzin NK (2012) Triangulation 2.0. J Mixed Methods Res 6(2):80–88. https://doi.org/10.1177/1558689812437186
Dixon-Román EJ (2016a) Diffracting enfolding futures: critical inquiry in quantitative educational research. Crit Educ 7(14):1–23. https://doi.org/10.14288/ce.v7i14.186147
Dixon-Román EJ (2016b) Diffractive possibilities: cultural studies and quantification. Transform Anthropol 24(2):157–167. https://doi.org/10.1111/traa.12074
Dixon-Román EJ (2017) Inheriting possibility: social reproduction and quantification in education. University of Minnesota Press, Minneapolis
Dixon-Román EJ (2020) A haunting logic of psychometrics: toward the speculative and indeterminacy of blackness in measurement. Educ Meas Issues Pract 39(3):94–96. https://doi.org/10.1111/emip.12375
Dunk RA (2020) Diffracting the “quantum” and the “social”: meeting the universe halfway in social science. Cult Stud Crit Methodol 20(3):225–234. https://doi.org/10.1177/1532708619880212
Faltermaier T (1997) Why public health research needs qualitative approaches: subjects and methods in change. Eur J Pub Health 7(4):357–363. https://doi.org/10.1093/eurpub/7.4.357
Fetters MD, Molina-Azorin JF (2021) Special issue on COVID-19 and novel mixed methods methodological approaches during catastrophic social changes. J Mixed Methods Res 15(3):295–303. https://doi.org/10.1177/15586898211029100
Foucault M (1991) On governmentality. In: Burchell G, Gordon C, Miller P (eds) The Foucault effects: studies in governmentality. Harvester Wheatsheaf, London, pp 87–104
Fox NJ (2016) Health sociology from post-structuralism to the new materialisms. Health 20(1):62–74. https://doi.org/10.1177/1363459315615393
Fox NJ, Alldred P (2021) Applied research, diffractive methodology, and the research-assemblage: challenges and opportunities. Sociol Res Online. https://doi.org/10.1177/13607804211029978
Gelman A, Carlin JB, Stern HS, Dunson DB, Vehtari A, Rubin DB (2013) Bayesian data analysis, 3rd edn. Chapman and Hall/CRC, New York. https://doi.org/10.1201/b16018
Giacomini MK (2001) The rocky road: qualitative research as evidence. BMJ Evid Based Med 6:4–6. https://doi.org/10.1136/ebm.6.1.4
Greene JC (2007) Mixed methods in social inquiry. Jossey-Bass, San Francisco
Greenland, S. (2019). Valid P-values behave exactly as they should: Some misleading criticisms of P-values and their resolution with S-values. The American Statistician, 73(sup1), 106–114. https://doi.org/10.1080/00031305.2018.1529625
Guyan K (2022) Queer data: using gender, sex and sexuality data for action. Bloomsbury Publishing, London
Hacking I (2006) The emergence of probability: a philosophical study of early ideas about probability induction and statistical inference, 2nd edn. Cambridge University Press, New York
Hall B, Howard K (2008) A synergistic approach: conducting mixed methods research with typological and systemic design considerations. J Mixed Methods Res 2(3):248–269. https://doi.org/10.1177/1558689808314622
Haraway D (1992) The promises of monsters: a regenerative politics for inappropriate/d others. In: Grossberg L, Nelson C, Treichler PA (eds) Cultural studies. Routledge, New York, pp 295–337
Haraway D (1997) Modest witness@second millennium-femaleman© meets oncomouse™: feminism and Technoscience. Routledge, New York
Hathcoat JD, Meixner C (2017) Pragmatism, factor analysis, and the conditional incompatibility thesis in mixed methods research. J Mixed Methods Res 11(4):433–449
Hesse-Biber SN (2010) Qualitative approaches to mixed methods practice. Qual Inq 16(6):455–468. https://doi.org/10.1177/1077800410364611
Hill CM (2017) More-than-reflective practice: becoming a diffractive practitioner. Teach Learn Prof Dev 2(1):1–17
Hooker S (2018, July 22) Why “data for good” lacks precision. [Blog post]. Retrieved from https://towardsdatascience.com/why-data-for-good-lacks-precision-87fb48e341f1
Howson C, Urbach P (1989) Scientific reasoning: the Bayesian approach. Open Court, La Salle
Inhorn MC, Whittle KL (2001) Feminism meets the “new” epidemiologies: toward an appraisal of antifeminist biases in epidemiological re- search on women’s health. Soc Sci Med 53(5):553–567. https://doi.org/10.1016/S0277-9536(00)00360-9
Kaiser BM, Thiele K (2014) Diffraction: onto-epistemology, quantum physics and the critical humanities. Parallax 30(3):165–167. https://doi.org/10.1080/13534645.2014.927621
Kass, R. E., & Raftery, A. E. (1995) Bayes factors. Journal of the American Statistical Association, 90, 773–795. https://doi.org/10.2307/2291091
Kirby V (2011) Quantum anthropologies: life at large. Duke University Press, Durham
Koikkalainen P (2011) Social inclusion. In: Bevir M (ed) The Sage handbook of governance. Sage, London
Krieger N (2001) Theories for social epidemiology in the 21st century: an ecosocial perspective. Int J Epidemiol 30:668–677. https://doi.org/10.1093/ije/30.4.668
Krieger N (2012) Methods for the scientific study of discrimination and health: an ecosocial approach. Am J Public Health 102(5):936–945. https://doi.org/10.2105/AJPH.2011.300544
Krieger N (2020) Measures of racism, sexism, heterosexism, and gender binarism for health equity research: from structural injustice to embodied harm – an ecosocial analysis. Annu Rev Public Health 41:37–62. https://doi.org/10.1146/annurev-publhealth-040119-094017
Krieger N (2021) Ecosocial theory, embodied truths, and the people’s health, Online edn. Oxford University Press, Oxford. https://doi.org/10.1093/oso/9780197510728.001.0001
Kukutai T, Walter M (2019) Indigenous statistics. In: Liamputtong P (ed) Handbook of research methods in health social sciences. Springer, Singapore
Lather P (2004) This is your father’s paradigm: government intrusion and the case of qualitative research in education. Qual Inq 10(1):15–34. https://doi.org/10.1177/1077800403256154
Lazar A, Jelen B, Pradhan A, Siek KA (2021) Adopting diffractive reading to advance hci research: a case study on technology for aging. ACM Trans Comput Hum Interact 28(5):1–29. https://doi.org/10.1145/3462326
Lenz Taguchi H (2012) A diffractive and Deleuzian approach to analysing interview data. Fem Theory 13(3):265–281. https://doi.org/10.1177/1464700112456001
Lenz Taguchi H, Palmer A (2013) A more ‘livable’ school? A diffractive analysis of the performative enactments of girls’ ill-/well-being with(in) school environments. Gend Educ 25(6):671–687. https://doi.org/10.1080/09540253.2013.829909
Lesaffre E, Lawson AB (2012) Bayesian biostatistics. Wiley, New York
Levy G, Halse C, Wright J (2016) Down the methodological rabbit hole: thinking diffractively with resistant data. Qual Res 16(2):183–197. https://doi.org/10.1177/1468794115571434
Liamputtong P (2022) Public health: local & global perspectives, 3rd edn. Cambridge University Press, Cambridge
Magnusson LO (2021) Visual research material and diffractive readings—a relational research story. J Qual Stud Educ 34(3):183–196. https://doi.org/10.1080/09518398.2020.1735564
Maxwell JA (2021) Why qualitative methods are necessary for generalization. Qual Psychol 8(1):111–118. https://doi.org/10.1037/qup0000173
Mazzei LA (2014) Beyond an easy sense: a diffractive analysis. Qual Inq 20(6):742–746. https://doi.org/10.1177/1077800414530257
McDermott E (2017) “Counting” for equality: youth, class and sexual citizenship. In: King A, Santos AC, Crowhurst I (eds) Sexualities research: critical interjections, diverse methodologies, and practical applications. Routledge, London, pp 44–57
McLaughlin H (2012) Understanding social work research, 2nd edn. Sage, Thousand Oaks. https://doi.org/10.4135/9781473913844
Meixner C, Spitzner DJ (2021) Social inclusion and mixed methods research. In: Liamputtong P (ed) Handbook of social inclusion. Springer, Cham
Mercier H, Sperber D (2011) Why do humans reason? Arguments for an argumentative theory. Behav Brain Sci 34(2):57–74
Mertens DM (2003) Mixed methods and the politics of human research: the transformative-emancipatory perspective. In: Tashakkori A, Teddlie C (eds) Handbook of mixed methods in social behavioral research. Sage, Thousand Oaks, pp 135–164
Mertens DM (2012) What comes first? The paradigm or the approach? J Mixed Methods Res 6(4):255–257
Mertens DM (2018) Mixed methods design in evaluation. Sage, Thousand Oaks
Mol A (2002) The body multiple: ontology in medical practice. Duke University Press, Durham
Murris K, Bozalek V (2019) Diffracting diffractive readings of texts as methodology: some propositions. Educ Philos Theory 51(14):1504–1517. https://doi.org/10.1080/00131857.2019.1570843
Nastasi B, Hitchcock J, Brown L (2010) An inclusive framework for conceptualizing mixed methods design typologies: moving toward fully integrated synergistic research models. In: Tashakkori A, Teddlie C (eds) Handbook of mixed methods in social & behavioral research. Sage, Thousand Oaks, pp 305–338
Nind M (2014) What is inclusive research? Bloomsbury, London
O’Hagan A, Buck CE, Daneshkhah A, Eiser JR, Garthwaite PH, Jenkinson DJ et al (2006) Uncertain judgements: eliciting experts’ probabilities. Wiley. https://doi.org/10.1002/0470033312
Padgett DK (2012) Qualitative and mixed methods in public health. Sage, Thousand Oaks. https://doi.org/10.4135/9781483384511
Palmer A (2011) “How many sums can I do”?: performative strategies and diffractive thinking as methodological tools for rethinking mathematical subjectivity. Reconceptualizing Educ Res Methodol 2(1). https://doi.org/10.7577/rerm.173
Parisi L, Dixon-Román EJ (2020) Data capitalism, sociogenic prediction, and recursive indeterminacies. In: Mörtenböck P, Mooshammer H (eds) Data publics: public plurality in an era of data determinacy. Routledge, New York, pp 48–62
Pienaar K, Moore D, Fraser S, Kokanovic R, Treloar C, Dilkes-Frayne E (2017) Diffracting addicting binaries: an analysis of personal accounts of alcohol and other drug ‘addiction’. Health 21(5):519–537. https://doi.org/10.1177/1363459316674062
Prah Ruger J (2020a) Positive public health ethics: toward flourishing and resilient communities and individuals. Am J Bioeth 20(7):44–54. https://doi.org/10.1080/15265161.2020.1764145
Prah Ruger J (2020b) Social justice as a foundation for democracy and health. BMJ 371(m4049):1–3. https://doi.org/10.1136/bmj.m4049
Pratt B (2021) Research for health justice: an ethical framework linking global health research to health equity. BMJ Glob Health 6(2):e002921. https://doi.org/10.1136/bmjgh-2020-002921
Randall J (2021) “Color-neutral” is not a thing: redefining construct definition and representation through a justice-oriented critical antiracist lens. Educ Meas Issues Pract 40(4):82–90. https://doi.org/10.1111/emip.12429
Redmayne M (2002) Appeals to reason. Mod Law Rev 65(1):19–35. https://doi.org/10.1111/1468-2230.00364
Riha J, Abreu Lopes C, Ibrahim NA, Srinivasan S (2021) Media and digital technologies for mixed methods research in public health emergencies such as COVID-19: lessons learned from using interactive radio-SMS for social research in Somalia. J Mixed Methods Res 15(3):304–326. https://doi.org/10.1177/1558689820986748
Rotman B (2000) Mathematics as sign: writing, imagining, counting. Stanford University Press, Stanford
Scheel S (2020) Biopolitical bordering: enacting populations as intelligible objects. Eur J Soc Theory 23(4):571–590. https://doi.org/10.1177/1368431019900096
Scott D (1995) Colonial governmentality. Social Text 43:191–220. https://doi.org/10.2307/466631
Smith ML (1997) Mixing and matching: methods and models. In: Greene JC, Caracelli VJ (eds) Advances in mixed-methods evaluation: the challenges and benefits of integrating diverse paradigms. Jossey-Bass Publishers, San Francisco, pp 73–85
Smith LT (2012) Decolonizing methodologies: research and indigenous peoples, 2nd edn. Zed Books, London/New York
Snipp CM (2016) What does data sovereignty imply: what does it look like? In: Kukutai T, Taylor J (eds) Indigenous data sovereignty: toward an agenda. Australian National University Press, Canberra
Spitzner DJ (2021) Socially-inclusive foundations of statistics. In: Liamputtong P (ed) Handbook of social inclusion. Springer, Cham. https://doi.org/10.1007/978-3-030-48277-017-1
Spitzner DJ (2022) A statistical basis for reporting strength of evidence as pool reduction. Am Stat. https://doi.org/10.1080/00031305.2022.2026478
Taylor CA, Gannon S (2018) Doing time and motion diffractively: academic life everywhere and all the time. J Qual Stud Educ 31(6):465–486. https://doi.org/10.1080/09518398.2017.1422286
Teddlie C, Tashakkori A (2003) Major issues and controversies in the use of mixed methods in the social and behavioral sciences. In: Tashakkori A, Teddlie C (eds) Handbook of mixed methods in social & behavioral research. Sage, Thousand Oaks, pp 3–50
Walter M, Andersen C (2013) Indigenous statistics: a quantitative research methodology. Left Coast Press, Walnut Creek
Watson A (2020) Methods braiding: a technique for arts-based and mixed-methods research. Sociol Res Online 25(1):66–83. https://doi.org/10.1177/1360780419849437
Wilson D, Neville S (2009) Culturally safe research with vulnerable populations. Contemp Nurse 33(1):69–79. https://doi.org/10.5172/conu.33.1.69
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Spitzner, D.J. (2023). Upending Quantitative Methodology for Use in Global Public Health. In: Liamputtong, P. (eds) Handbook of Social Sciences and Global Public Health. Springer, Cham. https://doi.org/10.1007/978-3-030-96778-9_51-1
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