Q methodology studies on human perspectives for biological conservation 1996-2017

DOI

This database synthesises peer-review articles that use Q methodology (an approach to understand human perspectives in a variety of topics) for research questions in biological conservation, from 1996 until 2017. The database was compiled to analyse how the methodology is being applied in conservation, what kind of research decisions were being made, and the quality of reporting, among others. Database of articles using this specific methodology. For each study, the database indicates a variety of characteristics of the study, such as context, goals, methodological decisions, etc. The database was compiled to analyse how the methodology is being applied in conservation, what kind of research decisions were being made, and the quality of reporting, among others.

Structured literature review of peer-reviewed papers using Q methodology in biological conservation research. Of global scope. The studies listed had a varied coverage, including local, sub-national, national, international and global. The list of articles and the protocol for their selection is detailed in the Supplementary Information of the associated peer-reviewed paper (see Related Resources). Briefly, the articles were sampled using keyword search in Scopus, Web of Science and the archives of ‘Operant Subjectivity’ (a journal specialized in Q but not indexed), covering biodiversity or conservation, during all years available (see the SI for the exact search string). For each study, the database indicates a variety of characteristics of the study, such as context, goals, methodological decisions, etc. (see variable description file).

Identifier
DOI https://doi.org/10.5255/UKDA-SN-854014
Metadata Access https://datacatalogue.cessda.eu/oai-pmh/v0/oai?verb=GetRecord&metadataPrefix=oai_ddi25&identifier=f76ad34505220f99fbc40738af470a4ef56be1b4b978aa663ca02714f955a7b6
Provenance
Creator Zabala, A, University of Cambridge; Mukherjee, N, University of Cambridge
Publisher UK Data Service
Publication Year 2020
Rights Aiora Zabala, University of Cambridge. Nibedita Mukherjee, University of Cambridge; The Data Collection is available to any user without the requirement for registration for download/access.
OpenAccess true
Representation
Resource Type Numeric; Text; Geospatial
Discipline Psychology; Social and Behavioural Sciences
Spatial Coverage World Wide