Comparative statistical analyses often require data harmonization, yet the social sciences do not have clear operationalization frameworks that guide and homogenize variable coding decisions across disciplines. When faced with a need to harmonize variables researchers often look for guidance from various international studies that employ output harmonization, such as the Comparative Survey of Election Studies, which offer recoding structures for the same variable (e.g. marital status). More problematically there are no agreed documentation standards or journal requirements for reporting variable harmonization to facilitate a transparent replication process. We propose a conceptual and data-driven digital solution that creates harmonization documentation standards for publication and scholarly citation: QuickCharmStats 1.1. It is free and open-source software that allows for the organizing, documenting and publishing of data harmonization projects. QuickCharmStats starts at the conceptual level and its workflow ends with a variable recording syntax. It is therefore flexible enough to reflect a variety of theoretical justifications for variable harmonization. Using the socio-demographic variable ‘marital status’, we demonstrate how the CharmStats workflow collates metadata while being guided by the scientific standards of transparency and replication. It encourages researchers to publish their harmonization work by providing researchers who complete the peer review process a permanent identifier. Those who contribute original data harmonization work to their discipline can now be credited through citations. Finally, we propose peer-review standards for harmonization documentation, describe a route to online publishing, and provide a referencing format to cite harmonization projects. Although CharmStats products are designed for social scientists our adherence to the scientific method ensures our products can be used by researchers across the sciences.
Modern microbial and ecosystem sciences require diverse interdisciplinary teams that are often challenged in “speaking” to one another due to different languages and data product types. Here we introduce the IsoGenie Database (IsoGenieDB; https://isogenie-db.asc.ohio-state.edu/), a de novo developed data management and exploration platform, as a solution to this challenge of accurately representing and integrating heterogenous environmental and microbial data across ecosystem scales. The IsoGenieDB is a public and private data infrastructure designed to store and query data generated by the IsoGenie Project, a ~10 year DOE-funded project focused on discovering ecosystem climate feedbacks in a thawing permafrost landscape. The IsoGenieDB provides (i) a platform for IsoGenie Project members to explore the project’s interdisciplinary datasets across scales through the inherent relationships among data entities, (ii) a framework to consolidate and harmonize the datasets needed by the team’s modelers, and (iii) a public venue that leverages the same spatially explicit, disciplinarily integrated data structure to share published datasets. The IsoGenieDB is also being expanded to cover the NASA-funded Archaea to Atmosphere (A2A) project, which scales the findings of IsoGenie to a broader suite of Arctic peatlands, via the umbrella A2A Database (A2A-DB). The IsoGenieDB’s expandability and flexible architecture allow it to serve as an example ecosystems database.
We use focus group transcripts from the innovative Qualitative Election Study of Britain dataset to provide insights into why 'Cleggmania' failed to translate into electoral success for the Liberal Democrats in 2010. Analyses conducted on participants' vote choice stories indicate the effect of 'Cleggmania' was limited to strengthening the resolve of wavering Liberal Democrats. Long-time Labour and Conservative supporters who leaned Liberal Democrat before the election found their latent party identification made voting for a different party psychologically uncomfortable. Qualitative electoral research can advance our understanding of people's voting calculus by analysing narratives for values, identity, utility maximizing, and constituency dynamics.
The Qualitative Election Study of Britain (QESB) is the first (and only) qualitative longitudinal dataset to investigate political attitudes and voting behaviour over multiple elections and referendums in the United Kingdom. During the 2015 UK general election over 90 voters participated in 23 focus groups across England, Scotland, and Wales before and after polling day. These participants represented a range of political party supporters and independent voters, age groups, and economic backgrounds. They discussed a range of political issues including their vote choice in the election, their impressions of the major party leaders, why they would consider voting (or never voting) for a political party, and their expectations for the country moving forward. Special focus groups were also held around the three leaders' debates. The 2015 QESB also brought back participants who had participated in the 2010 QESB focus groups and the 2014 Scottish referendum focus groups. The 2015 QESB has created a unique panel of participants whose political opinions can be tracked across multiple elections. The project also includes questions that were asked in prior election focus groups and has replicated, with some modifications, the research design of the previous wave of the study.
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