Biology Science Information Literacy: Primary/Secondary Sources, Peer Review, and Credibility
Source Credibility in Biology
Information sources in the modern landscape come from multiple channels: social media, YouTube, news outlets, radio, and Google searches. People increasingly rely on these platforms for news, information, and recommendations.
Key guiding question: How do we know we’re selecting credible sources, especially on social media where quality varies widely?
Takeaway: Credibility assessment is essential for biology (and general information) because sources differ dramatically in reliability and intent.
Primary vs Secondary Sources
Primary sources:
Definition: The original published research manuscript or data produced by the researchers conducting the work.
Characteristics: First-hand data, methods, results, and conclusions; designed to be concise yet detailed so others can replicate experiments or analyses.
Audience: Often not ideal for casual readers; requires some domain familiarity.
Access: Can be paywalled; libraries (e.g., university libraries) can provide free access via licenses.
Role in learning: Useful for high-fidelity evaluation of methods and data; cornerstone for reviews and meta-analyses.
Secondary sources:
Definition: Summaries or interpretations of primary research (e.g., reviews, summaries in news outlets, textbooks).
Pros and cons: More digestible for non-experts; can introduce bias or misinterpretation if not traced back to primary data.
Use case: Helpful for overviews but should be traced back to the primary sources for accuracy.
Practical note from lecture:
When locating primary sources for papers, use library resources (e.g., university libraries) to access papers without paywalls.
Example discussion in class involved identifying an article’s publisher (Springer Nature), journal section (e.g., Signal Transduction Targeted Therapy), and affiliations (Department of Breast Surgery, University of Shanghai Cancer Center, China).
The article’s bibliographic information includes authors, affiliations, and publication status (e.g., online publication date).
Important caveat: Publication venue and date matter; older papers may not reflect current understanding.
Peer Review and Its Importance
Peer review basics:
Manuscripts are evaluated by peers (experts in the field) before publication.
Reviewers assess methods, data integrity, results, conclusions, and whether discussions are well-founded.
Goal: Ensure data actually supports conclusions and that there is no data fabrication or falsification.
Definitions:
Falsification: Altering data to fit a desired conclusion.
Fabrication: Creating data that did not come from actual experiments.
Why it matters:
Peer review contributes to trust in scientific journals relative to non-peer-reviewed content (e.g., some social media sources).
Journals strive for concise yet detailed reporting to enable replication and validation by others using the same equipment and methods.
Reading a Primary Research Article: An Illustrative Example
Example discussed in class:
Article related to signal transduction and targeted therapy; published in a journal under the Springer Nature umbrella.
Authors affiliated with the Department of Breast Surgery and the University of Shanghai Cancer Center (from China).
Publication details discussed: online publication date; affiliation details at the bottom of the first page.
Access and verification considerations: how to locate author affiliations, origin, and institutional context.
Key checks when evaluating a primary article:
Who wrote it? What are their affiliations and institutional backing?
Where is it from (country, institution, lab)?
What is the funding source or potential sponsor influence? (See conflict of interest section.)
What is the publication venue (journal name, publisher) and its credibility?
The role of the journal’s structure:
Where is the conflict of interest/competing interests section? (Often near the end, before references.)
How does funding relate to findings and conclusions?
Conflict of Interest and Ethical Considerations
Location in the paper:
The conflict of interest or competing interests section appears in most primary articles, typically near the end, before the references.
Why it is important:
Disclosure promotes accountability and helps readers assess potential biases.
Example scenarios:
If a drug company funds a study, readers should check whether this could influence conclusions.
No conflict of interest disclosure is a red flag if undisclosed funding later emerges.
Consequences of undisclosed conflicts:
If disclosed later as a real conflict, the article can be retracted and researchers may face professional consequences.
Practical takeaway:
Always review the COI/competing interests section to understand potential biases and funding influences before accepting conclusions at face value.
Accessing Primary Sources: Library Services and Strategies
Why use libraries:
University libraries can provide access to primary literature that may be paywalled otherwise.
Libraries can indicate whether a given paper is available under the institution’s license, enabling free access for students.
How to use library resources:
Go to the library website and search for the paper by title or author.
If an exact copy isn’t available, check for interlibrary loan options or alternative repositories.
For coursework and reviews, verify you’re reading the primary source rather than a secondary summary.
Practical note from lecture:
Students were encouraged to use the library (e.g., the local university library) to access primary sources and avoid misinterpretation from paywalled articles.
Secondary Sources and News Outlets
Role of secondary sources:
They summarize primary research to make complex topics accessible.
They can help non-experts, but may introduce bias or misinterpretation if not carefully checked.
Examples of reputable outlets (as mentioned in the lecture):
National Geographic (natgeo.org), Smithsonian Magazine, and other established science news sources.
The transcript references several sources with some transcription errors (e.g., mentions like 'geo', 'North America', 'breakfast.org'); verify actual site names when possible.
Cautions about misinformation:
Secondary sources can propagate inaccuracies if they rely on misinterpreted primary data.
Always verify with the primary source when possible.
Yellowstone misinformation case:
Since 02/2017, Yellowstone scientists have received multiple inquiries about magma and volcanic risk.
A USA Today article in 2017 reported a potential for a supervolcano eruption; this was later corrected, clarifying the misinterpretation of a scientist’s conference discussion.
The “telephone game” effect (miscommunication through repeated retellings) can amplify fear-based narratives.
Media literacy takeaway:
Check credentials, potential biases, and funding sources.
Be cautious about sensational headlines that may oversimplify or misrepresent data.
Recognize that even reputable outlets can publish articles that require corrections or clarifications.
Social media and credibility:
Social media posts can spread personal anecdotes and misinformation.
If content is credible (e.g., from a credible institution), it’s more likely to be reliable; if from an influencer or commercial source, scrutinize credentials and potential conflicts.
The broader issue:
Science communication on social media is a growing field; there is a push to involve professionals to improve accuracy and counter misinformation.
Social Media, Influencers, and Misinformation: Case Studies and Implications
Influencers as information sources:
Liver King and other lifestyle influencers can promote medical or health claims without scientific validation.
Wildlife influencers (e.g., conservation-focused profiles) can raise awareness but may also misrepresent animal behavior or captivity status, potentially encouraging unsafe or misleading perceptions.
Risks and harms:
Medical misinformation leading to harmful health decisions.
Mental and public health harms from fear-based or sensational claims.
Misrepresentation of wildlife or ecological facts (e.g., confusing captive vs. wild animals on safari).
Ethical concerns:
Non-disclosure of expertise and credentials; promotion of products without evidence.
The need for professional presence on platforms to improve accuracy and curb misinformation.
Practical Guidance for Students and Researchers
How to critically engage with online biology information:
Always check the source’s credentials and potential biases.
Look for primary data, not just summaries or anecdotes.
Review the funding and competing interests disclosures.
Assess whether data are supported by methods and replicable experiments.
Be mindful of sensationalism and check for corrections or retractions.
How to responsibly use social media in scientific work:
Consider cross-checking information with primary sources before citing it.
Favor content from well-established institutions and journals.
Be cautious of posts that advocate for rapid medical decisions without evidence.
Assignment Preparation and Next Steps
Assigned readings (Health TikTok trends):
Read Health TikTok article PDF first.
Then follow the link to the second article on health information on TikTok.
What to extract from the readings:
How TikTok and other social media platforms disseminate health information.
Common misinformation tactics and how credible sources counter them.
Recommendations for evaluating social media health content and applying it to biology coursework or research.
Final reflections:
Consider how you would explain to a lay audience why primary sources are more trustworthy than anecdotal social media posts.
Practice identifying potential COI and assessing whether a source provides enough methodological detail to evaluate replicability.
Quick Reference Checklist
Is the article a primary source with original data and methods? If yes, read carefully and verify methods and data against conclusions.
Is there a clear conflict of interest/competing interests disclosure? If yes, read how funding might influence conclusions.
Can you access the article through your library or institutional subscription? If yes, use it rather than paywalled sites.
Is the source credible and free from obvious bias? Cross-check with other credible outlets and the primary source.
Are there examples of sensationalism or misinterpretation (e.g., telephone-game misreporting)? If so, seek the original data or peer-reviewed commentary.
When using social media for science information, verify credentials, look for data-backed claims, and be wary of product-promotion or anecdotal evidence.
Overview of course structure and classroom practices
Labs and lectures are not combined into a single grade; you will receive two separate grades for these classes.
Treat the lab like a film class as well; instructors may not update the lab frequently, and TAs or you will handle the lab page and labs themselves.
Attendance and participation are tracked via lab submissions; ensure your name is included on lab responses; if there are issues, speak with the instructor after class.
What is scientific inquiry? Core process and mindset
Observations lead to questions about natural phenomena (e.g., rocks moving in the Racetrack, Dry Lake).
Starting activity: look at a photo of drifting stones and brainstorm possible explanations, including natural and even fantastical hypotheses (e.g., wind, water, gravity, ghosts, aliens).
Students are expected to post group responses to show they were present and to share initial hypotheses; this also supports attendance tracking.
The class discussion showcases multiple plausible explanations and the value of considering different factors early in inquiry.
Emphasis on formulating hypotheses from observations and then testing them with data.
Case study: The drifting rocks of the Racetrack (Dry Lake)
Initial description in class: stones appear to move across the surface, leaving trails up to several hundred feet long, even though the area is typically dry.
Key quantitative details from the video narrative:
Rocks range from pebbles to up to ~600\text{ pounds}.
Trails can be as long as ~800\text{ feet}.
The Racetrack is surrounded by mountains; the surface is a dry lake bed.
A winter pond forms, then a thin layer of floating ice forms a wind-driven surface that can move ice sheets and drag rocks, creating trails beneath the ice.
The pond covered roughly the southern third of the racetrack; ice was a few millimeters thick; floating ice moved rocks that were in the pond, forming visible trails when the pond dried.
Trails can exist for a decade or more before the next pond forms and rocks move again.
The phenomenon is extremely rare because the racetrack is dry about 99% of the time.
Observers note that rocks may move slowly under ice and that movement is hard to observe in real time; sometimes several rocks move together, leaving few stationary traces.
Process of forming scientific understanding in this case:
Early hypotheses from observers (e.g., wind, water) were plausible but unconfirmed.
A dedicated observation campaign (Dick Norris and colleagues) finally witnessed rock movement during a rare pond event and ice conditions, allowing a better mechanistic explanation.
Conclusion: movement was driven by floating ice sheets moving in a shallow pond, which pushed rocks along as they moved; trails formed beneath the ice and were exposed as the pond drained.
Significance for science:
Demonstrates how hypotheses form from observations and how data (observations during a specific natural event) can revise explanations.
Highlights the rarity of certain phenomena and the need for the right conditions to observe them.
Shows that science is a dynamic process, not a static collection of facts.
How science works: hypotheses, data, revisions, and the role of time
Science uses hypotheses as testable explanations; they should be falsifiable, not unassailable.
As data accumulate, hypotheses are refined, revised, or replaced; this is a normal part of scientific progress.
A key point: science is not static; it evolves with new evidence and new questions.
The instructor uses metaphors and examples (e.g., ghosts in popular media) to illustrate what science can and cannot measure, reinforcing the idea that not all claims are scientifically testable.
Time as a variable: time is a common parameter in science, used to measure changes, rates, and processes.
Science, ethics, and the limits of scientific knowledge
Distinguishing science from moral and ethical questions:
Science describes how the world is (natural phenomena, mechanisms, data).
Ethics and morality describe how the world should be (values, policies, norms).
Science can inform ethical decisions by providing data, but it does not determine moral choices.
Science does not answer every question; there are domains (e.g., policy, rights, and moral principles) where non-scientific considerations come into play.
Discussions of policy relevance: once data are collected, scientists must consider how (or whether) to communicate provisional findings to the public, especially when data are incomplete and policies could be affected.
The process in practice: data analysis, reporting, and communication
After data collection, the steps are: analyze, conclude, and report results.
Reporting and communicating findings is essential; science is collaborative and builds on shared information.
Everyday example of scientific thinking in ordinary life:
A toothpaste switch caused throat reactions for the author; testing involved comparing Colgate vs Tom’s toothpaste and a control (no toothpaste), with careful consideration of variables and timing.
This illustrates testability, falsifiability, and the iterative nature of experimentation in daily decision-making.
Key concepts and terminology
Hypothesis: a proposed, testable explanation that can be supported or refuted by data.
Null hypothesis: a default position that there is no effect or difference; often denoted as H_0.
Alternative hypothesis: the hypothesis you test against the null, often denoted as H1 or Ha.
Falsifiability: a hypothesis must be capable of being proven false by data; otherwise, it is not scientific.
Theory: a well-substantiated, broadly supported explanation derived from a set of observations and multiple hypotheses; not declared
