abcnews.go.com
Data Nerds Fight Back Against Government Data Suppression
Concerned by the removal and alteration of U.S. government datasets under the Trump administration, statisticians, demographers, and computer scientists have formed groups to preserve and share the data, fearing that the removal of this data will hinder democracy and policymaking. This includes the creation of websites like dataindex.com, which monitors changes to federal data sets and the Data Rescue Project, which serves as a clearinghouse for data rescue-related efforts.
- What are the potential long-term consequences of these actions on public trust in government data and future research?
- The long-term impact of these actions could be a significant erosion of public trust in government data, hindering evidence-based policymaking and potentially affecting future research. The creation of independent data preservation groups highlights the critical need for robust safeguards against political interference with scientific data.
- What is the immediate impact of the removal and alteration of data from U.S. government websites on democracy and policymaking?
- Since January, the U.S. government has altered or removed data on topics like gender, health, and climate change from public websites. This has prompted statisticians and computer scientists to create a network to preserve these data sets, fearing that the removal of this data will negatively affect democracy. These actions have resulted in the loss of trillions of bytes of data, costing millions of public dollars.
- How are the actions taken by the U.S. government impacting the integrity of the nation's statistical system, and what are the broader implications?
- The removal of data from government websites is part of a broader pattern of actions taken that undermine the integrity of the U.S. statistical system. This includes job cuts of data guardians at statistical agencies and the alteration of public health datasets. Researchers have found that almost half of 232 federal public health data sets were substantially altered in the first quarter of this year.
Cognitive Concepts
Framing Bias
The narrative is framed around the actions of data preservation groups, emphasizing their efforts and concerns. This framing casts them in a positive light as heroes protecting essential data against political interference. While highlighting this side is important, it might overshadow other perspectives or the potential justifications for data alterations. The headline itself, "Data Nerds Fight Back", implies a conflict and positions the data preservers as protagonists. This framing may influence reader sympathy.
Language Bias
The language used is generally neutral, though terms like "army of outside statisticians" and "data warriors" are somewhat evocative, creating a sense of conflict and urgency. While conveying enthusiasm for data preservation, these terms slightly deviate from completely neutral reporting. Neutral alternatives could include "a group of statisticians" and "data preservationists".
Bias by Omission
The article focuses on the actions of data preservation groups and the challenges they face. While it mentions the alteration and disappearance of data sets, it does not delve into the specific details of what data is missing or altered beyond a few examples (gendesex change, discrimination question removal). A more comprehensive list of missing or altered data sets and their potential impact would provide a more complete picture. The omission of specific details may be due to space constraints or the focus on the actions of the data rescue groups.
False Dichotomy
The article presents a clear dichotomy between those who are preserving data and those who are altering or removing it. This framing simplifies a complex issue; it doesn't fully explore motivations behind data alteration or consider alternative interpretations of actions taken by government agencies. The article implies that all data changes are inherently negative and driven by partisan politics. This oversimplification may skew public understanding.
Sustainable Development Goals
The article highlights the removal of questions about discrimination based on gender or sexual identity from the National Survey of Children's Health. This suppression of data hinders research and understanding of crucial social issues, impacting the quality and comprehensiveness of education on these topics.