BEGIN:VCALENDAR VERSION:2.0 PRODID:-//pretalx//ifkw.rz.tu-bs.de//citizen-science-communication-trust-20 26//speaker//BQGJZB BEGIN:VTIMEZONE TZID:CET BEGIN:STANDARD DTSTART:20001029T040000 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=10 TZNAME:CET TZOFFSETFROM:+0200 TZOFFSETTO:+0100 END:STANDARD BEGIN:DAYLIGHT DTSTART:20000326T030000 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=3 TZNAME:CEST TZOFFSETFROM:+0100 TZOFFSETTO:+0200 END:DAYLIGHT END:VTIMEZONE BEGIN:VEVENT UID:pretalx-citizen-science-communication-trust-2026-QVYXRM@ifkw.rz.tu-bs.d e DTSTART;TZID=CET:20261006T110000 DTEND;TZID=CET:20261006T111500 DESCRIPTION:Introduction\nParticipatory approaches like citizen science can increase trust in science (e.g.\; Bedessem et al.\, 2021\, 2023\; Wintter lin et al.\, 2022)\, not least by enhancing people’s science self-concep t and science efficacy (PISA 2025 Science Framework\, 2025). Certain chara cteristics of citizen science projects can make these benefits more or les s likely to occur (Bonney et al.\, 2016\; Moczek & Köhler\, 2020)\, such as the role that involved citizens take on in the scientific process. Depe ndent on how citizen science practitioners conceptualise citizen science\, citizens may be seen primarily as data providers (Bonney\, 1996)\, or as collaborators in various aspects of scientific projects (Irwin\, 1995). Th eoretically\, projects guided by the second conceptualisation are more lik ely to increase trust in science by enhancing preconditions of trust betwe en career and citizen scientists (e.g.\, mutual respect\, connectedness\; Deci & Ryan\, 2012). In light of intense normative and theoretical debate around the concept of citizen science (e.g.\; Cooper et al.\, 2021)\, we a im to establish an empirical baseline of the status-quo of how citizen sci ence and related approaches (i.e.\, community and participatory science\, CCP) are currently conceptualised and implemented in the body of peer-revi ewed literature. Specifically\, we ask:\nRQ1: How are the terms citizen sc ience\, community science and participatory science referred to\, includin g their definitions\, aims\, and procedures\, in the contemporary body of peer-reviewed literature?\nRQ2: How are citizen science\, community scienc e\, and participatory science practiced in terms of the degree of citizen/ community/participatory scientist involvement?\nRQ3: Based on a theoretica l reflection of the findings\, how can the different approaches to involvi ng non-professional individuals in scientific research be expected to rela te to participants’ self-referential perceptions of science (e.g.\, scie nce self-concept\, science self-efficacy\, as defined in PISA 2025 Science Framework\, 2025)?\nMethods\nWe preregistered the study in line with the PRISMA protocol (Moher et al.\, 2015).\nSearch strategy\nWe searched SCOPU S\, Web of Science Core Collection\, and PubMed for the search terms “ci tizen scien*”\, “community scien*” or “participatory scien*” in title\, abstract\, or keywords\, published between 01.01.2021 and 13.11.20 25. Detailed inclusion and exclusion criteria are outlined in Table 1. To ensure feasibility\, we reduced the very large corpus (N = 9\,006) by draw ing a random sample of records (30%). \n[TABLE 1]\nData analysis plan\nScr eening. An interdisciplinary team of 11 coders (from psychology\, communic ation science\, microbiology\, and chemistry) will screen articles for eli gibility. Articles are eligible if they report on a CCP project and are pr imary research articles (see Table 1 for more details). Coders will screen articles independently once interrater reliability was established on 5% of the respective corpora of abstracts/full texts.\nCoding. For each eligi ble article\, we will code (1) how authors conceptualise CCP by extracting text excerpts where authors refer to CCP (RQ1)\, and (2) what elements of the scientific process CCP scientists were involved in\, ranging from res earch question development to results communication (RQ2\; see Table 2 for more details on coding constructs\; Heigl et al.\, 2020). \nData analysis . For RQ1\, we will perform inductive content analysis of the text excerpt s of conceptualisations of CCP science\, to see how authors of peer-review ed publications refer to these three terms. For RQ2\, we will present desc riptive statistics on which elements of the scientific process CCP scienti sts contributed to in the CCP projects. \nSoftware. Both coding and conten t analysis will be supported by a Large Language Model (LLM) with strict h uman oversight and conservative model settings (Bermejo et al.\, 2025\; Zi ems et al.\, 2024). LLMs are well-suited for these tasks\, as they have be en shown to perform similarly well as human coders in deductive and induct ive coding while operating in a time- and cost-effective manner (e.g.\; Ch ew et al.\, 2023\; Mathis et al.\, 2024). \nLastly\, for RQ3\, we link fin dings with relevant theory (Deci & Ryan\, 2012) to infer implications of c onceptualisations and involvement for CCP scientists’ science self-conce pt\, science self-efficacy\, enjoyment of science\, and instrumental motiv ation—constructs considered important correlates of trust in science (PI SA 2025 Science Framework\, 2025).\n[TABLE 2]\nOutlook\nWe expect to compl ete eligibility screening by the end of August\, and data extraction and a nalysis in September 2026. We thus expect to present initial results on th e contents of CCP conceptualisations (RQ1) and CCP scientist involvement ( RQ2)\, as well as potential psychological implications (RQ3). We will disc uss the implications of our findings for citizen science and trust\, as we ll as methodological choices\, such as the chosen databases or the exclusi on of grey literature. DTSTAMP:20260721T195217Z LOCATION:Room 1 SUMMARY:“More than words“: Conceptualisations of citizen science and re lated approaches in the contemporary peer-reviewed literature and their ps ychological implications - Julia Holzer\, Jana Köhler URL:https://ifkw.rz.tu-bs.de/citizen-science-communication-trust-2026/talk/ QVYXRM/ END:VEVENT END:VCALENDAR