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- ItemSupplemental Material for “Notable enough? The questioning of women’s biographies on Wikipedia”(2024) Martini, FranziskaTable I. Sample size Table II. Reliability coefficients Table III. Total and relative numbers of biographies nominated for deletion by specific criteria for notability Figure I. Percentage of users and their level of justification by their position and the biography’s gender Figure II. Numbers of German-language Wikipedia biographies by tagged gender category and year of creation Figure III. Number of deletion nominations (N = 396) per logged-in users (N = 158) Figure V. Number of decisions (N = 362) per administrator (N = 35) Figure IV. Number of discussions (N = 461) logged-in users (N = 608) participated in
- ItemSupplemental material for “Datafication Markers: Curation and User Network Effects on Mobilization and Polarization During Elections”(2023) Gagrčin, Emilija dc.contributor.author Ohme, Jakob dc.contributor.author Buttgereit, Lina dc.contributor.author Grünewald, FelixSupplemental material Table A1. Predicting campaign participation (cross-sectional) Table A2. Predicting campaign participation (auto-regressive) Table A3. Predicting vote choice certainty (cross-sectional) Table A4. Predicting vote choice certainty (auto-regressive) Table A5. Predicting turnout (cross-sectional) Table A6. Predicting turnout (auto-regressive) Table A7. Predicting attitude reinforcement (change variable) Table A8. Predicting affective polarization (cross-sectional) Table A8. Predicting affective polarization (cross-sectional)
- ItemSupplementary data for “Why, with whom, and how to conduct interdisciplinary research? A review from a researcher’s perspective”(2024) Vladova, Gergana dc.contributor.author Haase, Jennifer dc.contributor.author Friesike, SaschaSupplementary data Table 1: Overview of the paper included in the data analysis. (Essential papers in bold) Table 2: Overview of the coding scheme
- ItemSupplementary Material for “Crossers in a Segmented Labour Market: Occupational Advancement and Wage Changes from Semi-Skilled and Unskilled Jobs”(2024) Wotschack, Philip dc.contributor.author Samtleben, Claire### Appendix Tab. 3.1: Descriptives (‘stayers’ and ‘movers’) Tab. 3.2: Descriptives (‘stayers’ only) Tab. 4: Logistic regression: Factors influencing career advancement (‘stayers’ and ‘movers’) Tab. 5: OLS regression analysis: Factors influencing wage changes (‘stayers’ and ‘movers’)
- ItemSupplementary Material for “Algorithmic media use and algorithm literacy: An integrative literature review“(2024) Gagrčin, Emilija dc.contributor.author Naab, Teresa K. dc.contributor.author Grub, Maria F.+ Table: First Order Categories, Higher Order Themes, Integrative Dimensions + Full sample of articles considered in the literature review + SM-Table 1. Dimensions of algorithm literacy according to Oeldorf-Hirsch and Neubaum (2023) and manifestations in the reviewed literature + SM-Table 2. Factors shaping algorithm literacy and manifestations in the reviewed literature + SM-Table 3. Outcomes of algorithm literacy