{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,6]],"date-time":"2026-09-06T04:10:34Z","timestamp":1788667834636,"version":"build-2803163510"},"reference-count":93,"publisher":"SAGE Publications","license":[{"start":{"date-parts":[[2026,9,3]],"date-time":"2026-09-03T00:00:00Z","timestamp":1788393600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,9,3]],"date-time":"2026-09-03T00:00:00Z","timestamp":1788393600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"DOI":"10.13039\/501100000155","name":"Social Sciences and Humanities Research Council of Canada","doi-asserted-by":"publisher","award":["767-2021-2798"],"award-info":[{"award-number":["767-2021-2798"]}],"id":[{"id":"10.13039\/501100000155","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Perspect Psychol Sci"],"abstract":"<jats:p>The shift to a society organized around digital data has come with significant\u2014although sometimes still underappreciated\u2014implications for psychological research. In part, this is owed to the narrowness of discussions about data ethics in the discipline, although also to the ontological assumptions about data that implicitly shape researchers\u2019 discussions and practices. The prevailing representationalist ontology of data\u2014understanding data to be a passive abstraction that represents some preexisting phenomenon\u2014draws researchers\u2019 attention to methodological issues, such as data quality, while simultaneously turning attention away from different kinds of issues. Informed by feminist technoscience and feminist-new-materialist thinkers, we argue for an alternative ontology of data that helps understand it as being material-relational\u2014as something that is active and entangles researchers in (often invisible) relations that have real, material consequences. These ontological commitments can draw attention to those relations and their implications and help researchers consider what ethical issues are at stake, thus creating the conditions to advocate for new kinds of responsible research practices. We put this ontology to work by looking at two issues: the labor problems from data collection on MTurk and the environmental impacts of data storage. We conclude by offering practical recommendations for more responsible data practices in psychology.<\/jats:p>","DOI":"10.1177\/17456916261471511","type":"journal-article","created":{"date-parts":[[2026,9,3]],"date-time":"2026-09-03T16:22:34Z","timestamp":1788452554000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["A Material-Relational Ontology of Data: Addressing Ethical Challenges in Psychological Research in a Data-Driven Era"],"prefix":"10.1177","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0881-1273","authenticated-orcid":false,"given":"Alexis","family":"Fabricius","sequence":"first","affiliation":[{"name":"Department of Psychology, University of Guelph"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8084-7097","authenticated-orcid":false,"given":"Jeffery","family":"Yen","sequence":"additional","affiliation":[{"name":"Department of Psychology, University of Guelph"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9242-2061","authenticated-orcid":false,"given":"Kieran","family":"O\u2019Doherty","sequence":"additional","affiliation":[{"name":"Department of Psychology, University of Guelph"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maya","family":"Goldenberg","sequence":"additional","affiliation":[{"name":"Department of Philosophy, University of Guelph"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2026,9,3]]},"reference":[{"key":"e_1_3_5_2_1","doi-asserted-by":"crossref","unstructured":"Adjerid I. Kelley K. (2018). Big data in psychology: A framework for research advancement. American Psychologist 73(7) 899\u2013917. https:\/\/doi.org\/10.1037\/amp00001","DOI":"10.1037\/amp0000190"},{"key":"e_1_3_5_3_1","unstructured":"Amazon.com Inc. (2026). Amazon.com announces fourth quarter results. https:\/\/ir.aboutamazon.com\/news-release\/news-release-details\/2026\/Amazon-com-Announces-Fourth-Quarter-Results\/"},{"key":"e_1_3_5_4_1","volume-title":"Publication manual of the American Psychological Association","author":"American Psychological Association","year":"2020","unstructured":"American Psychological Association. (2020) Publication manual of the American Psychological Association (7th ed.).","edition":"7"},{"key":"e_1_3_5_5_1","doi-asserted-by":"crossref","unstructured":"Atenas J. Havemann L. Timmermann C. (2023). Reframing data ethics in research methods education: A pathway to critical data literacy. International Journal of Educational Technology in Higher Education 20 Article 11. https:\/\/doi.org\/10.1186\/s41239-023-00380-y","DOI":"10.1186\/s41239-023-00380-y"},{"key":"e_1_3_5_6_1","doi-asserted-by":"publisher","DOI":"10.1215\/9780822388128"},{"key":"e_1_3_5_7_1","doi-asserted-by":"crossref","unstructured":"Barends A. J. de Vries R. E. (2019). Noncompliant responding: Comparing exclusion criteria in MTurk personality research to improve data quality. Personality and Individual Differences 143 84\u201389. https:\/\/doi.org\/10.1016\/j.paid.2019.02.015","DOI":"10.1016\/j.paid.2019.02.015"},{"key":"e_1_3_5_8_1","volume-title":"Data and society","author":"Beaulieu A.","year":"2021","unstructured":"Beaulieu A., Leonelli S. (2021). Data and society. Sage."},{"key":"e_1_3_5_9_1","doi-asserted-by":"crossref","unstructured":"Benbunan-Fich R. (2023). To pay or not to pay? Handling crowdsourced participants who drop out from a research study. Ethics and Information Technology 25(34) 1\u201314. https:\/\/doi.org\/10.1007\/s10676-023-09708-8","DOI":"10.1007\/s10676-023-09708-8"},{"key":"e_1_3_5_10_1","doi-asserted-by":"publisher","DOI":"10.1215\/9780822391623"},{"key":"e_1_3_5_11_1","unstructured":"Berg J. Furrer M. Harmon E. Rani U. Silberman M. S. (2018). Digital labour platforms and the future of work: Towards decent work in the online world. International Labour Organization. https:\/\/www.ilo.org\/wcmsp5\/groups\/public\/\u2014dgreports\/\u2014dcomm\/\u2014publ\/documents\/publication\/wcms_645337.pdf"},{"key":"e_1_3_5_12_1","doi-asserted-by":"publisher","DOI":"10.4337\/9781802205138.00013"},{"key":"e_1_3_5_13_1","doi-asserted-by":"crossref","unstructured":"Bezuidenhout L. Ratti E. (2021). What does it mean to embed ethics in data science? An integrative approach based on microethics and virtues. AI & Society 36 939\u2013953. https:\/\/doi.org\/10.1007\/s00146-020-01112-w","DOI":"10.1007\/s00146-020-01112-w"},{"key":"e_1_3_5_14_1","doi-asserted-by":"crossref","unstructured":"Bohannon J. (2016). Mechanical Turk upends social sciences. Science 352(6291) 1263\u20131264. https:\/\/doi.org\/10.1126\/science.352.6291.1263","DOI":"10.1126\/science.352.6291.1263"},{"key":"e_1_3_5_15_1","doi-asserted-by":"crossref","unstructured":"Borghi J. A. Van Gulick A. E. (2021). Data management and sharing: Practices and perceptions of psychology researchers. PLOS ONE 16(5) Article e0252047. https:\/\/doi.org\/10.1371\/journal.pone.0252047","DOI":"10.1371\/journal.pone.0252047"},{"key":"e_1_3_5_16_1","doi-asserted-by":"publisher","DOI":"10.7551\/mitpress\/9963.001.0001"},{"key":"e_1_3_5_17_1","doi-asserted-by":"crossref","unstructured":"boyd d. Crawford K. (2012). Critical questions for big data: Provocations for a cultural technological and scholarly phenomenon. Information Communication & Society 15(5) 662\u2013679. https:\/\/doi.org\/10.1080\/1369118X.2012.678878","DOI":"10.1080\/1369118X.2012.678878"},{"key":"e_1_3_5_18_1","doi-asserted-by":"crossref","unstructured":"Brodie P. (2023). Data infrastructure studies on an unequal planet. Big Data & Society 10(1). https:\/\/doi.org\/10.1177\/20539517231182402","DOI":"10.1177\/20539517231182402"},{"key":"e_1_3_5_19_1","doi-asserted-by":"crossref","unstructured":"Buhrmester M. D. Talaifar S. Gosling S. D. (2018). An evaluation of Amazon\u2019s Mechanical Turk its rapid rise and its effective use. Perspectives on Psychological Science 13(2) 149\u2013154. https:\/\/doi.org\/10.1177\/1745691617706516","DOI":"10.1177\/1745691617706516"},{"key":"e_1_3_5_20_1","unstructured":"Canadian Psychological Association. (2017). Canadian code of ethics for psychologists (4th ed.). https:\/\/cpa.ca\/docs\/File\/Ethics\/CPA_Code_2017_4thEd.pdf"},{"key":"e_1_3_5_21_1","unstructured":"CANARIE. (n.d.). Canada\u2019s National Research and Education Network. https:\/\/www.canarie.ca\/nren\/"},{"key":"e_1_3_5_22_1","doi-asserted-by":"crossref","unstructured":"Chamberlain J. (2011). Adam D.I. Kramer Facebook data scientist. gradPSYCH Magazine. American Psychological Association. https:\/\/www.apa.org\/gradpsych\/2011\/01\/kramer","DOI":"10.1037\/e669902010-003"},{"key":"e_1_3_5_23_1","doi-asserted-by":"crossref","unstructured":"Chandhirmowuli S. Chadhuri B. (2023). Match made by humans: A critical enquiry into human-machine configurations in data labelling. In Proceedings of the 56th Hawaii International Conference on System Sciences (pp. 2007\u20132016). https:\/\/doi.org\/10.24251\/HICSS.2023.251","DOI":"10.24251\/HICSS.2023.251"},{"key":"e_1_3_5_24_1","doi-asserted-by":"crossref","unstructured":"Chen E. Wojcik S. P. (2016). A practical guide to big data research in psychology. Psychological Methods 21(4) 458\u2013474. https:\/\/doi.org\/10.1037\/met0000111","DOI":"10.1037\/met0000111"},{"key":"e_1_3_5_25_1","doi-asserted-by":"publisher","DOI":"10.2307\/j.ctv1ghv45t"},{"key":"e_1_3_5_26_1","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511524059"},{"key":"e_1_3_5_27_1","unstructured":"European Commission. (n.d.). European Open Science Cloud (EOSC). https:\/\/research-and-innovation.ec.europa.eu\/strategy\/strategy-research-and-innovation\/our-digital-future\/open-science\/european-open-science-cloud-eosc_en"},{"key":"e_1_3_5_28_1","doi-asserted-by":"crossref","unstructured":"Ewim D. R. E. Nunduwezuor-Ehiobu N. Orikpete O. F. Egbokhaebho B. A. Fawole A. A. Onunka C. (2023). Impact of data centers on climate change: A review of energy efficient strategies. The Journal of Engineering and Exact Sciences 9(6) Article 16397\u201301e. https:\/\/doi.org\/10.18540\/jcecvl9iss6pp16397-01e","DOI":"10.18540\/jcecvl9iss6pp16397-01e"},{"key":"e_1_3_5_29_1","unstructured":"Fabricius A. (2025). Re-imagining our data futures: A material-relational ontology for a Big Tech era [Doctoral dissertation]. The Atrium. https:\/\/hdl.handle.net\/10214\/29171"},{"key":"e_1_3_5_30_1","doi-asserted-by":"crossref","unstructured":"Fabricius A. O\u2019Doherty K. Yen J. (2026). Data ethics and the Canadian Code of Ethics for Psychologists. Canadian Psychology 67(1) 33\u201342. https:\/\/doi.org\/10.1037\/cap0000440","DOI":"10.1037\/cap0000440"},{"key":"e_1_3_5_31_1","unstructured":"Fairwork. (2025). Fairwork Cloudwork ratings 2025: Advancing standards in digital labour and AI supply chain governance. Oxford Internet Institute University of Oxford. https:\/\/fair.work\/wp-content\/uploads\/sites\/17\/2025\/05\/Fairwork-Cloudwork-Report-2025-FINAL.pdf"},{"key":"e_1_3_5_32_1","doi-asserted-by":"crossref","unstructured":"Favaretto M. De Clercq E. Gaab J. Elger B. S. (2020). First do no harm: An exploration of researchers\u2019 ethics of conduct in Big Data behavioral studies. PLOS ONE 15(11) Article e0241865. https:\/\/doi.org\/10.1371\/journal.pone.0241865","DOI":"10.1371\/journal.pone.0241865"},{"key":"e_1_3_5_33_1","doi-asserted-by":"crossref","unstructured":"Fiske A. Henningsen P. Buyx A. (2019). Your robot therapist will see you now: Ethical implications of embodied artificial intelligence in psychiatry psychology and psychotherapy. Journal of Medical Internet Research 21(5) Article e13216. https:\/\/doi.org\/10.2196\/13216","DOI":"10.2196\/13216"},{"key":"e_1_3_5_34_1","doi-asserted-by":"crossref","unstructured":"Fleischer A. Mead A. D. Huang J. (2015). Inattentive responding in MTurk and other online samples. Industrial and Organizational Psychology 8(2) 196\u2013202. https:\/\/doi.org\/10.1017\/iop.2015.25","DOI":"10.1017\/iop.2015.25"},{"key":"e_1_3_5_35_1","doi-asserted-by":"crossref","unstructured":"Floridi L. Taddeo M. (2016). What is data ethics? Philosophical Transactions of the Royal Society A: Mathematical Physical and Engineering Sciences 374 Article 20160360. https:\/\/doi.org\/10.1098\/rsta.2016.0360","DOI":"10.1098\/rsta.2016.0360"},{"key":"e_1_3_5_36_1","doi-asserted-by":"crossref","unstructured":"Fowler C. Jiao J. Pitts M. (2023). Frustration and ennui among Amazon MTurk workers. Behaviour Research Methods 55 3009\u20133023. https:\/\/doi.org\/10.3758\/s13428-022-01955-9","DOI":"10.3758\/s13428-022-01955-9"},{"key":"e_1_3_5_37_1","doi-asserted-by":"crossref","unstructured":"Fuchs C. (2014). Digital prosumption labour on social media in the context of the capitalist regime of time. Time & Society 23(1) 97\u2013123. https:\/\/doi.org\/10.1177\/0961463X13502117","DOI":"10.1177\/0961463X13502117"},{"key":"e_1_3_5_38_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-658-14681-8_10"},{"key":"e_1_3_5_39_1","doi-asserted-by":"crossref","unstructured":"Furner J. (2016). \u201cData\u201d: The data. In Kelly M. Bielby J. (Eds.) Information cultures in the digital age: A festschrift in honor of Rafael Capurro (pp. 287\u2013306). Springer. https:\/\/doi.org\/10.4337\/9781035304233.00008","DOI":"10.4337\/9781035304233.00008"},{"key":"e_1_3_5_40_1","doi-asserted-by":"crossref","unstructured":"Gandini A. (2021). Digital labour: An empty signifier? Media Culture & Society 43(2) 369\u2013380. https:\/\/doi.org\/10.1177\/0163443720948018","DOI":"10.1177\/0163443720948018"},{"key":"e_1_3_5_41_1","unstructured":"Gonzalez-Monserrate S. (2022 February 14). The staggering ecological impacts of computation and the cloud. The MIT Press Reader. https:\/\/thereader.mitpress.mit.edu\/the-staggering-ecological-impacts-of-computation-and-the-cloud\/"},{"key":"e_1_3_5_42_1","doi-asserted-by":"crossref","unstructured":"Grosz E. Hill R. (2017). Onto-ethics and difference: An interview with Elizabeth Grosz. Australian Feminist Law Journal 43(1) 5\u201314. https:\/\/doi.org\/10.1080\/13200968.2017.1317203","DOI":"10.1080\/13200968.2017.1317203"},{"key":"e_1_3_5_43_1","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511814563"},{"key":"e_1_3_5_44_1","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511819766"},{"key":"e_1_3_5_45_1","doi-asserted-by":"crossref","unstructured":"Hakimi L. Eynon R. Murphy V. A. (2021). The ethics of using digital trace data in education: A thematic review of the research landscape. Review of Educational Research 91(5) 671\u2013717. https:\/\/doi.org\/10.3102\/00346543211020116","DOI":"10.3102\/00346543211020116"},{"key":"e_1_3_5_46_1","unstructured":"Han Y. Wu Z. Li P. Wierman A. Ren S. (2024). The unpaid toll: Quantifying the public health impact of AI. arXiv. https:\/\/doi.org\/10.48550\/arXiv.2412.06288"},{"key":"e_1_3_5_47_1","doi-asserted-by":"publisher","DOI":"10.1215\/9780822373780"},{"key":"e_1_3_5_48_1","unstructured":"IEA. (2023). Data centres and data transmission networks. https:\/\/www.iea.org\/energy-system\/buildings\/data-centres-and-data-transmission-networks"},{"key":"e_1_3_5_49_1","unstructured":"IEA. (2025a). Aviation. https:\/\/www.iea.org\/energy-system\/transport\/aviation"},{"key":"e_1_3_5_50_1","unstructured":"IEA. (2025b). Energy demand from AI. https:\/\/www.iea.org\/reports\/energy-and-ai\/energy-demand-from-ai"},{"key":"e_1_3_5_51_1","doi-asserted-by":"crossref","unstructured":"Ienca M. Vayena E. (2021). Is it ethical to use hacked data in scientific research? SSRN. https:\/\/doi.org\/10.2139\/ssrn.3843733","DOI":"10.2139\/ssrn.3843733"},{"key":"e_1_3_5_52_1","unstructured":"Jessop S. Volcovici V. Mukherjee S. (2026 April 6). Investors press Amazon Microsoft and Google on water power use in US data centres. Reuters. https:\/\/www.reuters.com\/sustainability\/boards-policy-regulation\/investors-press-amazon-microsoft-google-water-power-use-us-data-centers-2026-04-06\/"},{"key":"e_1_3_5_53_1","doi-asserted-by":"crossref","unstructured":"Kim A. Y. Escobedo-Land A. (2015). OkCupid Data for introductory statistics and data science courses. Journal of Statistics Education 23(2). https:\/\/doi.org\/10.1080\/10691898.2015.11889737","DOI":"10.1080\/10691898.2015.11889737"},{"key":"e_1_3_5_54_1","doi-asserted-by":"publisher","DOI":"10.4135\/9781473909472"},{"key":"e_1_3_5_55_1","doi-asserted-by":"crossref","unstructured":"Kosinski M. Wang Y. Lakkaraju H. Leskovec J. (2016). Mining big data to extract patterns and predict real-life outcomes. Psychological Methods 21(4) 493\u2013506. https:\/\/doi.org\/10.1037\/met0000105","DOI":"10.1037\/met0000105"},{"key":"e_1_3_5_56_1","doi-asserted-by":"crossref","unstructured":"Kramer A. D. I. Guillroy J. E. Hancock J. T. (2014). Experimental evidence of massive-scale emotional contagion through social networks. Proceedings of the National Academy of Sciences 111(24) 8788\u20138870. https:\/\/doi.org\/10.1073\/pnas.1320040111","DOI":"10.1073\/pnas.1320040111"},{"key":"e_1_3_5_57_1","doi-asserted-by":"crossref","unstructured":"Lei N. Lu J. Shehabi A. Masanet E. (2025). The water use of data center workloads: A review and assessment of key determinants. Resources Conservation and Recycling 219 Article 108310. https:\/\/doi.org\/10.1016\/j.resconrec.2025.108310","DOI":"10.1016\/j.resconrec.2025.108310"},{"key":"e_1_3_5_58_1","first-page":"191","volume-title":"The Routledge handbook of philosophy of information","author":"Leonelli S.","year":"2016","unstructured":"Leonelli S. (2016). The philosophy of data. In Floridi L. (Ed.), The Routledge handbook of philosophy of information (pp. 191\u2013202). Routledge."},{"key":"e_1_3_5_59_1","doi-asserted-by":"crossref","unstructured":"Lucivero F. (2020). Big Data big waste? A reflection on the environmental sustainability of Big Data initiatives. Science and Engineering Ethics 26(2) 1009\u20131030. https:\/\/doi.org\/10.1007\/s11948-019-00171-7","DOI":"10.1007\/s11948-019-00171-7"},{"key":"e_1_3_5_60_1","doi-asserted-by":"crossref","unstructured":"Martone M. E. Garcia-Catro A. VandenBos G. R. (2018). Data sharing in psychology. American Psychologist 73(2) 111\u2013125. https:\/\/doi.org\/10.1037\/amp0000242","DOI":"10.1037\/amp0000242"},{"key":"e_1_3_5_61_1","doi-asserted-by":"crossref","unstructured":"McInnis B. Cosley D. Nam C. Leshed G. (2016). Taking a HIT: Designing around rejection mistrust risk and workers\u2019 experiences in Amazon Mechanical Turk. In Design Labour and the Invisible Perils of Crowdsourcing CHI 2016 (pp. 2271\u20132282). Association for Computing Machinery. https:\/\/doi.org\/10.1145\/2858036.2858539","DOI":"10.1145\/2858036.2858539"},{"key":"e_1_3_5_62_1","doi-asserted-by":"crossref","unstructured":"Metcalf J. Crawford K. (2016). Where are human subjects in Big Data research? The emerging ethics divide. Big Data and Society 3(1). https:\/\/doi.org\/10.1177\/2053951716650211","DOI":"10.1177\/2053951716650211"},{"key":"e_1_3_5_63_1","doi-asserted-by":"publisher","DOI":"10.1215\/9780822384151"},{"key":"e_1_3_5_64_1","doi-asserted-by":"crossref","unstructured":"Moss A. J. Rosenzweig C. Robinson J. Jaffe S. N. Litman L. (2023). Is it ethical to use Mechanical Turk for behavioral research? Relevant data from a representative survey of MTurk participants and wages. Behavior Research Methods 55(8) 4048\u20134067. https:\/\/doi.org\/10.3758\/s13428-022-02005-0","DOI":"10.3758\/s13428-022-02005-0"},{"key":"e_1_3_5_65_1","unstructured":"Newman A. (2019 November 15). I found work on an Amazon website. I made 97 cents an hour. The New York Times. https:\/\/www.nytimes.com\/interactive\/2019\/11\/15\/nyregion\/amazon-mechanical-turk.html"},{"key":"e_1_3_5_66_1","doi-asserted-by":"crossref","unstructured":"O\u2019Doherty K. C. Fairley C. Badulescu D. Fabricius A. (2024). Analyzing discourse for implicit ontologies. Qualitative Psychology 11(2) 294\u2013314. https:\/\/doi.org\/10.1037\/qup0000293","DOI":"10.1037\/qup0000293"},{"key":"e_1_3_5_67_1","unstructured":"Osaka S. (2023 April 25). A new front in the water wars: Your internet use. The Washington Post. https:\/\/www.washingtonpost.com\/climate-environment\/2023\/04\/25\/data-centers-drought-water-use\/"},{"key":"e_1_3_5_68_1","doi-asserted-by":"crossref","unstructured":"Paruzel-Czachura M. Baran L. Spendel Z. (2020). Publish or be ethical? Publishing pressure and scientific misconduct in research. Research Ethics 17(3) 375\u2013397. https:\/\/doi.org\/10.1177\/1747016120980562","DOI":"10.1177\/1747016120980562"},{"key":"e_1_3_5_69_1","doi-asserted-by":"crossref","unstructured":"Paxton A. (2020). The Belmont Report in the age of big data: Ethics at the intersection of psychological science and data science. In Woo S. E. Tay L. Proctor R. W. (Eds.) Big data in psychological research (pp. 347\u2013372). American Psychological Association. https:\/\/doi.org\/10.1037\/0000193-016","DOI":"10.1037\/0000193-016"},{"key":"e_1_3_5_70_1","doi-asserted-by":"crossref","unstructured":"Pittman M. Sheehan K. (2016). Amazon\u2019s Mechanical Turk a digital sweatshop? Transparency and accountability in crowdsourced online research. Journal of Media Ethics 31(4) 260\u2013262. https:\/\/doi.org\/10.1080\/23736992.2016.1228811","DOI":"10.1080\/23736992.2016.1228811"},{"key":"e_1_3_5_71_1","doi-asserted-by":"crossref","unstructured":"Prainsack B. El-Sayed S. Forg\u00f3 N. Szoszkiewicz L. Baumer P. (2022). Data solidarity: A blueprint for governing health futures. The Lancet Digital Health 4(11) e773\u2013e774. https:\/\/doi.org\/10.1016\/S2589-7500(22)00189-3","DOI":"10.1016\/S2589-7500(22)00189-3"},{"key":"e_1_3_5_72_1","doi-asserted-by":"crossref","unstructured":"Radin J. (2017). \u201cDigital natives\u201d: How medical and Indigenous histories matter for big data. Osiris 32(1) 43\u201364. https:\/\/doi.org\/10.1086\/693853","DOI":"10.1086\/693853"},{"key":"e_1_3_5_73_1","unstructured":"Rogoway M. (2022 December 20). Google\u2019s water use is soaring in The Dalles with more data centers to come. The Seattle Times. https:\/\/www.oregonlive.com\/silicon-forest\/2022\/12\/googles-water-use-is-soaring-in-the-dalles-records-show-with-two-more-data-centers-to-come.html"},{"key":"e_1_3_5_74_1","doi-asserted-by":"crossref","unstructured":"Rosenberg D. (2013). Data before the fact. In Gitelman L. (Ed.) \u201cRaw data\u201d is an oxymoron (pp. 15\u201340). The MIT Press. https:\/\/doi.org\/10.7551\/mitpress\/9302.003.0003","DOI":"10.7551\/mitpress\/9302.003.0003"},{"key":"e_1_3_5_75_1","unstructured":"Sattiraju N. (2020 April 1). Google data centers\u2019 secret cost: Billions of gallons of water. Bloomberg. https:\/\/www.bloomberg.com\/news\/features\/2020-04-01\/how-much-water-do-google-data-centers-use-billions-of-gallons"},{"key":"e_1_3_5_76_1","unstructured":"Semuels A. (2018 January 23). The internet is enabling a new kind of poorly paid hell. The Atlantic. https:\/\/www.theatlantic.com\/business\/archive\/2018\/01\/amazon-mechanical-turk\/551192\/?source=post_page"},{"key":"e_1_3_5_77_1","doi-asserted-by":"crossref","unstructured":"Sharon T. Lucivero F. (2019). Introduction to the Special Theme: The expansion of the health data ecosystem \u2013 Rethinking data ethics and governance. Big Data & Society 6(2). https:\/\/doi.org\/10.1177\/2053951719852969","DOI":"10.1177\/2053951719852969"},{"key":"e_1_3_5_78_1","doi-asserted-by":"crossref","unstructured":"Siddik M. A. B. Shehabi A. Marston L. (2021). The environmental footprint of data centers in the United States. Environmental Research Letters 16(6) Article 064017. https:\/\/doi.org\/10.1088\/1748-9326\/abfba1","DOI":"10.1088\/1748-9326\/abfba1"},{"key":"e_1_3_5_79_1","doi-asserted-by":"crossref","unstructured":"Silberman M. S. Tomlinson B. LaPlante R. Ross J. Irani L. Zaldivar A. (2018). Responsible research with crowds: Pay crowdworkers at least minimum wage. Communications of the ACM 61(3) 39\u201341. https:\/\/doi.org\/10.1145\/3180492","DOI":"10.1145\/3180492"},{"key":"e_1_3_5_80_1","doi-asserted-by":"crossref","unstructured":"Stewart R. (2021). Big data and Belmont: On the ethics and research implications of consumer-based datasets. Big Data & Society 8(2). https:\/\/doi.org\/10.1177\/20539517211048183","DOI":"10.1177\/20539517211048183"},{"key":"e_1_3_5_81_1","unstructured":"SURF. (n.d.). Energy smart computing. https:\/\/www.surf.nl\/en\/energy-smart-computing"},{"key":"e_1_3_5_82_1","unstructured":"The White House. (2025 July 16). ICYMI: President Trump announces $92 + billion in AI energy powerhouse investments. https:\/\/www.whitehouse.gov\/releases\/2025\/07\/icymi-president-trump-announces-92-billion-in-ai-energy-powerhouse-investments\/"},{"key":"e_1_3_5_83_1","doi-asserted-by":"crossref","unstructured":"Tubaro P. Casilli A. A. Coville M. (2020). The trainer the verifier the imitator: Three ways in which human platform workers support artificial intelligence. Big Data & Society 7(1). https:\/\/doi.org\/10.1177\/2053951720919776","DOI":"10.1177\/2053951720919776"},{"key":"e_1_3_5_84_1","doi-asserted-by":"crossref","unstructured":"Tugtekin U. Barut Tugtekin E. (2025). Influential factors on academics\u2019 digital hoarding behaviours: An exploratory PLS-SEM research. Behaviour & Information Technology 44(8) 1667\u20131680. https:\/\/doi.org\/10.1080\/0144929X.2024.2368701","DOI":"10.1080\/0144929X.2024.2368701"},{"key":"e_1_3_5_85_1","doi-asserted-by":"publisher","DOI":"10.1093\/acprof:oso\/9780190498511.001.0001"},{"issue":"2","key":"e_1_3_5_86_1","first-page":"187","article-title":"Digital archiving, green IT and environment: Deleting data to manage critical effects of the data deluge","volume":"18","author":"van Bussel G.","year":"2015","unstructured":"van Bussel G., Smit N., van de Pas J. (2015). Digital archiving, green IT and environment: Deleting data to manage critical effects of the data deluge. The Electronic Journal of Information Systems Evaluation, 18(2), 187\u2013198.","journal-title":"The Electronic Journal of Information Systems Evaluation"},{"key":"e_1_3_5_87_1","doi-asserted-by":"crossref","unstructured":"van Maanen G. (2022). AI ethics ethics washing and the need to politicize data ethics. DISO 1(9). https:\/\/doi.org\/10.1007\/s44206-022-00013-3","DOI":"10.1007\/s44206-022-00013-3"},{"key":"e_1_3_5_88_1","doi-asserted-by":"publisher","DOI":"10.7551\/mitpress\/14703.001.0001"},{"key":"e_1_3_5_89_1","doi-asserted-by":"crossref","unstructured":"Xiao T. Ma Y. (2021). A letter to the Journal of Statistics and Data Science Education \u2014 A call for review of \u201cOkCupid Data for Introductory Statistics and Data Science Courses\u201d by Albert Y. Kim and Adriana Escobedo-Land. Journal of Statistics and Data Science Education 29(2) 214\u2013215. https:\/\/doi.org\/10.1080\/26939169.2021.1930812","DOI":"10.1080\/26939169.2021.1930812"},{"key":"e_1_3_5_90_1","unstructured":"Ya\u00f1ez-Barnuevo M. (2026). Data centre power demands are contributing to higher energy bills. Environmental and Energy Study Institute. https:\/\/www.eesi.org\/articles\/view\/data-center-power-demands-are-contributing-to-higher-energy-bills"},{"key":"e_1_3_5_91_1","doi-asserted-by":"crossref","unstructured":"Yen J. (2024). The social life of digital methods in psychology: Situating digital methods in the new data politics. Social and Personality Psychology Compass 18(1) Article e12923. https:\/\/doi.org\/10.1111\/spc3.12923","DOI":"10.1111\/spc3.12923"},{"key":"e_1_3_5_92_1","doi-asserted-by":"crossref","unstructured":"Zhao Y. Du D. (2022). Research orientation and development of social psychology\u2019s concept of justice in the era of cloud computing. Frontiers in Psychology 13 Article 902780. https:\/\/doi.org\/10.3389\/fpsyg.2022.902780","DOI":"10.3389\/fpsyg.2022.902780"},{"key":"e_1_3_5_93_1","volume-title":"Surveillance capitalism","author":"Zuboff S.","year":"2019","unstructured":"Zuboff S. (2019a). Surveillance capitalism. Public Affairs."},{"key":"e_1_3_5_94_1","doi-asserted-by":"publisher","DOI":"10.7551\/mitpress\/11304.003.0006"}],"container-title":["Perspectives on Psychological Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/17456916261471511","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.1177\/17456916261471511","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/17456916261471511","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,6]],"date-time":"2026-09-06T03:29:00Z","timestamp":1788665340000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1177\/17456916261471511"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9,3]]},"references-count":93,"alternative-id":["10.1177\/17456916261471511"],"URL":"https:\/\/doi.org\/10.1177\/17456916261471511","relation":{},"ISSN":["1745-6916","1745-6924"],"issn-type":[{"value":"1745-6916","type":"print"},{"value":"1745-6924","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,9,3]]},"article-number":"17456916261471511"}}