ReviewOne earth (Cambridge, Mass.)2022
Expanding collaborative autoethnography into the world of natural science for transdisciplinary teams.
Review in One earth (Cambridge, Mass.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Article
- Pathways and identity: toward qualitative research careers in child and adolescent psychiatry.Child and adolescent psychiatry and mental health · 2024Article
- A conceptional game theory analysis of environmental public interest litigation of China.Heliyon · 2024Article
- The use of Messenger for research collaboration: An auto-ethnographic study.Frontiers in psychology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Wicked problems such as climate change and the COVID-19 pandemic require authentically transdisciplinary approaches to achieving effective collaboration. There exist several research approaches for identifying the components and interactions of complex problems; however, collaborative autoethnography provides an empirical way to collect and analyze self-reflection that leads to transformative change. Here, we present a case study of collaborative autoethnography, applied as a tool to transform research practice among a group of natural and social scientists, by constructively revealing and resolving deep, often unseen, disciplinary divides. We ask, "How can natural and social scientists genuinely accept, respect, and share one another's approaches to work on the wicked problems that need to be solved?" This study demonstrates how disciplinary divisions can be successfully bridged by open-minded and committed collaborators who are prepared to recognize the academic bias they bring to their research and use this as a platform of strength.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.