skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


Title: Credibility via Coupling: Institutions and Infrastructures in Climate Model Intercomparisons
This study investigates Model Intercomparison Projects (MIPs) as one example of a coordinated approach to establishing scientific credibility. MIPs originated within climate science as a method to evaluate and compare disparate climate models, but MIPs or MIP-like projects are now spreading to many scientific fields. Within climate science, MIPs have advanced knowledge of: a) the climate phenomena being modeled, and b) the building of climate models themselves. MIPs thus build scientific confidence in the climate modeling enterprise writ large, reducing questions of the credibility or reproducibility of any single model. This paper will discuss how MIPs organize people, models, and data through institution and infrastructure coupling (IIC). IIC involves establishing mechanisms and technologies for collecting, distributing, and comparing data and models (infrastructural work), alongside corresponding governance structures, rules of participation, and collaboration mechanisms that enable partners around the world to work together effectively (institutional work). Coupling these efforts involves developing formal and informal ways to standardize data and metadata, create common vocabularies, provide uniform tools and methods for evaluating resulting data, and build community around shared research topics.  more » « less
Award ID(s):
1929757
PAR ID:
10356858
Author(s) / Creator(s):
Date Published:
Journal Name:
Engaging Science, Technology, and Society
Volume:
7
Issue:
2
ISSN:
2413-8053
Page Range / eLocation ID:
10 to 32
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; ; (, Computational Journalism C+J)
    null (Ed.)
    Concerns about the spread of misinformation online via news articles have led to the development of many tools and processes involving human annotation of their credibility. However, much is still unknown about how different people judge news credibility or the quality or reliability of news credibility ratings from populations of varying expertise. In this work, we consider credibility ratings from two “crowd” populations: 1) students within journalism or media programs, and 2) crowd workers on UpWork, and compare them with the ratings of two sets of experts: journalists and climate scientists, on a set of 50 climate-science articles. We find that both groups’ credibility ratings have higher correlation to journalism experts compared to the science experts, with 10-15 raters to achieve convergence. We also find that raters’ gender and political leaning impact their ratings. Among article genre of news/opinion/analysis and article source leaning of left/center/right, crowd ratings were more similar to experts respectively with opinion and strong left sources. 
    more » « less
  2. ; ; ; (, Computational Journalism Symposium)
    Concerns about the spread of misinformation online via news articles have led to the development of many tools and processes involving human annotation of their credibility. However, much is still unknown about how different people judge news credibility or the quality or reliability of news credibility ratings from populations of varying expertise. In this work, we consider credibility ratings from two “crowd” populations: 1) students within journalism or media programs, and 2) crowd workers on UpWork, and compare them with the ratings of two sets of experts: journalists and climate scientists, on a set of 50 climate-science articles. We find that both groups’ credibility ratings have higher correlation to journalism experts compared to the science experts, with 10-15 raters to achieve convergence. We also find that raters’ gender and political leaning impact their ratings. Among article genre of news/opinion/analysis and article source leaning of left/center/right, crowd ratings were more similar to experts respectively with opinion and strong left sources. 
    more » « less
  3. ; ; ; ; (, Disciplinary and Interdisciplinary Science Education Research)
    Peer-review and publication are important parts of the scientific enterprise, and research has shown that engaging students in such scholarly practices helps build their sense of belonging and scientific identity. Yet, these disciplinary literacy skills and professional practices are often part of the hidden curriculum of science research, thus excluding students and others from fully understanding ways in which scientific knowledge is constructed, refined, and disseminated even though students are participating in such activities. Secondary students are increasingly involved in scientific research projects that include authentic disciplinary literacy components such as research proposals, posters, videos, and scientific research papers. More and more, students are also engaging in professional practice of publishing their scientific research papers through dedicated secondary science journals. How teachers and other mentors support the development of professional disciplinary literacies in students is critical to understand as part of supporting more student participation in research. To this end, we used a mixed-methods study of interviews and surveys to examine the experience and conceptions of the mentors (teachers and professional scientists) who guided pre-college students through the writing and publication of their scientific research projects. Analyzing our data from a lens of cognitive apprenticeship, we find that mentors encourage independence by primarily employing the method of “exploration”. We also find that mentors have divergent views on the value of publication within science, versus for student scientists specifically. Our findings suggest that mentors could work to explicitly reveal their own thinking within science writing to provide more sequenced support for student scientists. 
    more » « less
  4. (, Geoscientific model development)
    The General Lake Model (GLM) is a one-dimensional open-source model code designed to simulate the hydrodynamics of lakes, reservoirs and wetlands. GLM was developed to support the science needs of the Global Lake Ecological Observatory Network (GLEON), a network of lake sensors and researchers attempting to understand lake functioning and address questions about how lakes around the world vary in response to climate and land-use change. The scale and diversity of lake types, locations and sizes, as well as the observational data within GLEON, created the need for a robust community model of lake dynamics with sufficient flexibility to accommodate a range of scientific and management needs of the GLEON community. This paper summarises the scientific basis and numerical implementation of the model algorithms, including details of sub-models that simulate surface heat exchange and ice-cover dynamics, vertical mixing and inflow/outflow dynamics. A summary of typical parameter values for lakes and reservoirs collated from a range of sources is included. GLM supports a dynamic coupling with biogeochemical and ecological modelling libraries for integrated simulations of water quality and ecosystem health. An overview of approaches for integration with other models, and utilities for the analysis of model outputs and for undertaking sensitivity and uncertainty assessments is also provided. Finally, we discuss application of the model within a distributed cloud-computing environment, and as a tool to support learning of network participants. 
    more » « less
  5. ; ; (, Data Science Journal)
    We studied 11 long-term data infrastructure projects, most of which focused on the Earth Sciences, to understand characteristics that contributed to their project sustainability. Among our sample group, we noted the existence of three different types of project groupings: Database, Framework, and Middleware. Most efforts started as federally funded research projects, and our results show that nearly all became organizations in order to become sustainable. Projects were often funded for short time scales but had the long-term burden of sustaining and supporting open science, interoperability, and community building–activities that are difficult to fund directly. This transition from ‘project’ to ‘organization’ was challenging for most efforts, especially in regard to leadership change and funding issues.Some common approaches to sustainability were identified within each project grouping. Framework and Database projects both relied heavily on the commitment to, and contribution from, a disciplinary community. Framework projects often used bottom-up governance approaches to maintain the active participation and interest of their community. Database projects succeeded when they were able to position themselves as part of the core workflow for disciplinary-specific scientific research. Middleware projects borrowed heavily from sustainability models used by software companies, while maintaining strong scientific partnerships. Cyberinfrastructure for science requires considerable resources to develop and sustain itself, and much of these resources are provided through in-kind support from academics, researchers, and their institutes. It is imperative that more work is done to find appropriate models that help sustain key data infrastructure for Earth Science over the long-term. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email