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The effects of narrative framing of own broken love on understanding the past and imagining the future in close relationships
The dataset originates from a two-stage experimental study examining the effects of narrative framing of one’s past romantic relationship on thinking about the past relationship and future in close relationships. Participants were women aged 18–30 after a breakup (N = 422), randomly assigned to the narrative set (writing a self-story of broken love) or the control set (answering open questions about the past relationship). Stage 1 included the pretest and experimental manipulation; Stage 2 (after approximately one week) involved follow-up self-reports (including declared breakup understanding) and open-ended responses describing breakup reasons and thoughts on the future in close relationships. The dataset includes demographic, relationship, and experimental variables; qualitative evaluations of open-ended responses (participation quality, plot structuring of self-stories, coherence of breakup reasons descriptions, and content of thoughts on the future in close relationships); self-report psychological measures (Frequency of thoughts: counterfactual and future-oriented, Event-Related Rumination Inventory, and Declared Understanding of Breakup Reasons); and linguistic indices from computational analyses using LIWC and LEM tools for participants’ open responses to tasks from Stage 2. The collection includes publicly available files (Dataset.sav, trained coders instructions – Supporting Information S1–S5) and restricted-access files (participants’ open-ended responses available upon request). Access to the open-ended responses is restricted to justified academic requests and may be granted only for research purposes, under confidentiality and data protection conditions. License: CC BY 4.0 – Attribution. All data are fully anonymized. We want to express our deepest gratitude to the trained coders and research assistants—Natalia Dziombowska, Łukasz Florczak, Agata Kiszelewska, Klaudia Pastwa, Kaja Sławek, Tomasz Sławek—for their invaluable help with research materials preparation and work on coding the qualitative data. We also thank Agnieszka Młyniec, Ph.D., for contributing to the enhancements of the plot structuring scale and Assoc. Prof. Elżbieta Zdankiewicz-Ścigała, Ph.D., for help in obtaining study funding.Dane badawczeOtwarte dane badawcze Data about 2023 Sejm elections, county level
Data on county (powiat) level in Poland. The data was compiled from public sources. Turbout and party vote in Sejm elections on 15 Oct. 2023: National Electoral Comission (PKW) Earnings and unemployment: Central Statistical Office (GUS) Religious participation: Institute for statistics of the Catholic Church (ISKK)Dane badawczeOtwarte dane badawcze Projekt badawczy: Przekraczając (nie)widzialne granice. Doświadczenie awansu klasowego w biografiach jednostek (MINIATURA 2020/04/X/HS6/00399)
Udostępniane materiały (zestawienie 30 narratorów i narratorek, z którymi zrealizowane zostały wywiady; scenariusz wywiadu, oraz transkrypcje wywiadów z osobami, które wyraziły zgodę na archiwizację) pochodzą z projektu badawczego "Przekraczając (nie)widzialne granice. Doświadczenie awansu klasowego w biografiach jednostek" (NCN MINIATURA 2020/04/X/HS6/00399), realizowanego w latach 2020-2021 w Uniwersytecie Wrocławskim. Projekt ten stanowił pilotaż i obecnie jest rozwijany w ramach projektu "RaM-CLASS. Reprodukcja i mobilność klasowa – doświadczenia biograficzne w polach akademii, sztuki i biznesu" (NCN SONATA 2022/47/D/HS6/00726). Wywiady zebrane w projekcie pilotażowym są poddawane dalszej analizie. W ramach obu projektów gromadzone były wywiady biograficzno-narracyjne z naukowcami/naukowczyniami, artystami/artystkami, menadżerami/menadżerami biznesu. W ramach MINIATURY zbierane były wywiady z osobami, które doświadczyły międzypokoleniowego awansu klasowego.Dane badawczeOtwarte dane badawcze Data on the development and assessment of policy briefs co-created with genAI
Data set contains: (1) Record of three prompting sessions with genAI to co-create policy briefs (sessions B, C, and D); (2) Instructions to experts and a package of 4 policy briefs to be assessed (Policy briefs A, B, C, and D); (3) Results of assessments made by 15 experts.Dane badawczeOtwarte dane badawcze Neural Mechanisms and Efficacy of Imagery Rescripting for Fear of Failure: A Randomized Controlled Trial
Data from the study Neural Mechanisms and Efficacy of Imagery Rescripting for Fear of Failure: A Randomized Controlled Trial, financed by the National Science Centre (grant number 2018/30/E/HS6/00703 Sonata Bis 8). The dataset contains demographic data, intervention data, and the extracted BOLD signal from the ROI. The whole fMRI dataset, organized using BIDS, can be accessed here (due to the size of the whole BIDS dataset, it is kept on the Google drive): https://drive.google.com/drive/folders/1iA9v5s9hvRRqZhXULEtxr9YpVGV2Eym8?usp=sharing For full access, please contact Principal Investigator, Professor Jarosław Michałowski ([email protected]), or Stanisław Karkosz ([email protected]). This work was produced in whole or in part by SWPS University researchers and is subject to the SWPS University Intellectual property policy. For the purpose of Open Access the author has applied a CC BY public copyright license to any Author Accepted Manuscript version arising from this submission. This research was funded in whole or in part by the National Science Centre (grant number 2018/30/E/HS6/00703 Sonata Bis 8. For the purpose of Open Access, the author has applied a CC-BY public copyright license to any Author Accepted Manuscript (AAM) version arising from this submission.Dane badawczeOtwarte dane badawcze