Stoic Dedication and Scientific Discovery

Stoic Dedication and Scientific Discovery: Lessons from Jane Goodall and the Philosophy of Inquiry

This document, written by Dr. Denis Jacob Machado on October 2, 2025, is inspired by discussions on the lives and works of Jane Goodall, Charles S. Peirce, Karl Popper, Willi Hennig, and the Stoic philosophers Epictetus, Seneca, and Marcus Aurelius. It is intended as an accessible reflection for early-career researchers and students.

Introduction

Science often advances through patient, methodical effort—driven not by profit but by curiosity and courage. Few embody this spirit better than Dr. Jane Goodall, whose lifelong study of chimpanzees transformed our understanding of primate behavior and inspired generations of scientists and activists. This document examines the philosophical foundations of scientific inquiry, the importance of fundamental research, and the role of stoic perseverance, drawing on examples from Goodall and influential thinkers such as Peirce, Popper, Hennig, and the Stoics.

The Philosophy of Scientific Inquiry

Modern science blends several reasoning modes—abduction, induction, and deduction—in a cycle of discovery, testing, and refinement. These concepts were explored in depth by Charles Sanders Peirce (1839–1914), a logician and philosopher from the United States who coined the term abduction.

Definition: Abduction is the process of generating the most plausible explanation for an observation. It is the logic of forming hypotheses based on incomplete evidence. Definition: Induction involves identifying patterns in specific observations to infer general rules or theories. Definition: Deduction applies general rules to specific cases to predict outcomes or validate observations.

Peirce emphasized that inquiry starts with abduction, proceeds to deductive testing, and ends with inductive confirmation—but the cycle repeats as new observations arise, indicating a discrepancy of some sort.

Abduction, Deduction, and Induction as Part of the Discovery Process

Abduction (within the world of facts) is the inference to the best explanation. When we observe a fact and try to come up with the most plausible explanation for it, we are engaging in abductive reasoning. Abduction begins in the world of facts and tries to generate a likely rule or hypothesis that could explain what we’re seeing—even if we don’t have complete information. It’s the starting point of inquiry, where creativity meets plausibility.

An example of abductive reasoning, inspired by Dr. Goodall, is: “We observe that chimpanzees use sticks to extract termites. We abduct that they must understand the stick’s function as a tool.”

Induction (from the world of facts to the world of rules) is generalizing from examples. Inductive reasoning is when we look at repeated observations or patterns and infer a general rule or principle. It moves from the world of facts to the creation of rules. However, these rules are always provisional in the sense that they are supported by evidence but not guaranteed.

For example: “We observe many chimpanzees across years using tools. We induce the rule that chimpanzees, as a species, use tools.”

Deduction (within the language of rules) is applying rules to specific cases. Deductive reasoning begins with a general rule or theory and applies it to a specific situation to draw a logically certain conclusion. It operates entirely within the world of rules and tests whether a specific case follows logically.

For example: “All species that use tools exhibit flexible problem-solving. Chimpanzees use tools. Therefore, we deduce that chimpanzees exhibit flexible problem-solving.”

Karl Popper and the Power of Falsification

Karl Popper (1902–1994), an Austrian-British philosopher, argued that what defines science is not confirmation, but falsification—the ability to test and potentially refute hypotheses.

Definition: Falsification is a scientific theory must make predictions that can be proven wrong. If a theory cannot be tested or falsified, it does not belong to science.

Popper’s insistence on falsifiability shifted the focus of science to deductive rigor and bold theorizing. He critiqued inductive confirmation as always fallible, stressing that no number of positive observations can guarantee a theory is true—yet a single counterexample can disprove it.

Stoic Endurance in Scientific Life

Stoicism, a school of philosophy founded in Ancient Greece, teaches resilience, self-discipline, and focus on what one can control. Its best-known Roman advocates include:

• Epictetus (c. 50–135 CE): Born a slave, he taught that inner freedom comes from mastering desires.
• Seneca (4 BCE–65 CE): A tutor to Nero who emphasized rationality and moral clarity even under pressure.
• Marcus Aurelius (121–180 CE): A Roman emperor whose Meditations are a personal journal on remaining calm and virtuous amid turmoil.

Definition: Stoicism is a philosophy of life that emphasizes controlling one’s responses, accepting fate with equanimity, and acting according to reason and virtue.

Dr. Jane Goodall: A Stoic in the Field

Jane Goodall (b. 1934, England) was not trained as a conventional scientist but began observing chimpanzees in Tanzania in 1960. Despite skepticism from the male-dominated academic community, she persisted for years without recognition. Her discovery that chimpanzees make and use tools overturned prior assumptions about human uniqueness.

Dr. Jane Goodall, who chronicled the social lives of chimps, passed at 91 on October, 2025. Her discoveries as a primatologist in the 1960s about how chimpanzees behave in the wild were hailed by Dr. Stephen Jay Gould, the evolutionary biologist and science historian, as “one of the Western world’s great scientific achievements.”

Her approach embodies stoic patience, humility, and dedication to truth. Goodall’s work was not funded by corporations seeking products, but by public institutions and philanthropic science foundations, such as the Leakey Foundation and National Geographic Society.

Her research ultimately led to:

• Protection efforts for endangered chimpanzees
• Educational programs via the Jane Goodall Institute
• Influence on animal welfare laws and conservation science

Definition: Fundamental Research is a curiosity-driven research aimed at understanding basic principles or phenomena, without immediate commercial application. Often funded by public or academic institutions. Examples of Fundamental Research with Impact include: Goodall’s primate studies (animal rights legislation, environmental policy), CRISPR gene editing (originated from bacterial immunity research), and the internet (born from academic interest in distributed computing).

Dr. Goodman as a Hero Fighting the Bandwagon Effect

Definition: Bandwagon Effect is the tendency to adopt certain beliefs or behaviors because many others have already adopted them. It reflects our instinct to conform, avoid exclusion, and align with the “winning” or popular side.

In addition to her scientific achievements, Dr. Jane Goodall stands as a symbol of resistance to a powerful cognitive bias: the bandwagon effect. This bias reflects our tendency to adopt beliefs or behaviors simply because they are popular—because “everyone else is doing it.”

Goodall’s early work in Gombe defied both academic and cultural expectations. At a time when few women were leading scientific fieldwork—and when most primatologists favored detached, quantitative methods—Goodall immersed herself in the lives of chimpanzees. She gave them names, observed them closely, and shared their stories with the world. Her approach, combining rigorous observation with emotional connection, was initially criticized as unscientific. Yet she persisted, and eventually changed the field of primatology forever.

She also rejected the prevailing belief that non-human animals were little more than instinct-driven automatons. By documenting chimpanzees using tools, expressing emotion, and forming social bonds, she challenged the status quo—and the world took notice.

Importantly, Goodall turned her research into a narrative, one that invited the public to see chimps not as experimental subjects but as beings with minds and lives of their own. Through television specials, books, and public speaking, she forged a new path that didn’t require scientific conformity to win respect. She became a global icon not because she followed the crowd, but because she courageously stood apart from it.

Lesson: Resisting the bandwagon effect is not just about thinking differently—it’s about being willing to stand alone when necessary. Goodall’s legacy reminds us that original insights often come from those who are willing to question consensus, follow their observations, and think for themselves.

More on the Bandwagon Effect and Groupthink

Definition: Groupthink is a psychological phenomenon where members of a group suppress dissenting opinions to maintain harmony or avoid conflict, often resulting in poor decisions.

The bandwagon effect is common in politics, medicine, education, marketing, investing, and even science itself. It often masquerades as common sense: “If so many people believe this, it must be true.” But as researchers have shown, this can lead us to accept flawed ideas and suppress critical thought.

Consider a sports fan who switches teams simply because the new team is winning, or a voter who changes allegiance after seeing a poll. These examples might seem trivial, but the consequences can scale rapidly. Medical professionals, for instance, have historically embraced unproven procedures (like widespread tonsillectomies) simply because they were popular at the time—not because they were backed by strong evidence.

Why does the Bandwagon Effect happen? It happens because of natural (and evolutionarily beneficial) mental shortcuts (heuristic processes). Popularity is used as a proxy for truth. Moreover, social conformity dictates that we seek inclusion and avoid isolation. Finally, we all have an inherited desire to win. Therefore, aligning with the majority can feel safer or more advantageous.

When unchecked, the bandwagon effect contributes to mob mentality, suppression of dissent, and poor decision-making. It is closely related to:

Both biases erode individual critical thinking, especially in high-stakes or high-pressure environments. When people feel they can’t express minority opinions without facing backlash, they may remain silent—a dynamic known as the spiral of silence. This doesn’t just shape behavior; it shapes what we think we’re allowed to say, even to ourselves.

BONUS: Bandwagon Effect and A.I.

The explosive rise of AI offers a modern case study of the bandwagon effect. As “machine learning,” “deep learning,” “generative A.I.,” and other related terms become buzzwords, companies (and universities) rush to brand products as “A.I.-powered”—even when the features add little value. Why? Because the bandwagon is rolling, and consumers, investors, and developers alike don’t want to be left behind.

But adoption without discernment can be wasteful or even harmful. Voice assistants that fail, algorithms that misdiagnose, and overly complex “smart” devices that replace simpler solutions are all reminders that popular doesn’t mean practical.

Lesson: In a world flooded with trends and hype, slowing down our decision-making is a form of intellectual courage. Good ideas don’t always come with popular backing—and popular ideas aren’t always good.

Digression: A Shamelles Plug of Phylogenetics

Will Hennig (1913–1976), a German entomologist, revolutionized biological classification with his work on cladistics, a method for reconstructing evolutionary relationships based on shared derived characters (synapomorphies).

Definition: Cladistics Phylogenetics is a scientific method that classifies organisms based on the most recent common ancestor, using shared derived traits (synapomorphies) to define evolutionary lineages.

Definition: Synapomorphy is a trait shared by two or more taxa and inferred to be present in their most recent common ancestor. It distinguishes a clade from other lineages. It is a homologous characteristic that represents a type of similarity due to a shared evolutionary history.

Cladistics relies on:

• Abduction: Proposing evolutionary trees that best explain trait distributions.
• Deduction: Predicting unseen relationships or testing tree congruence.
• Induction: Accumulating support from multiple traits or datasets.

Hennig’s approach emphasized rigor and transparency, aligning with Popper’s falsification criterion—trees must make testable predictions.

Final Thoughts: Lessons for the Next Generation

• Curiosity is powerful: Major scientific shifts often begin with quiet, careful observation—not flashy innovations.
• Be patient: Like Goodall and Hennig, breakthroughs take years, sometimes decades.
• Value uncertainty: Science is a cycle of hypothesis, test, refinement. It thrives on humility.
• Practice stoicism: Focus on effort, not reward. Be resilient in the face of slow progress or rejection.
• Defend fundamental research: It’s the bedrock of long-term innovation, from health to conservation to AI.

Don’t Forget:

• Abduction starts the process (guessing).
• Deduction tests the guess.
• Induction generalizes from results.
• Falsification is how science sharpens truth.
• Synapomorphies build trees, not similarities alone.
• Stoicism keeps you grounded when the work is slow or uncertain.
• Fundamental research drives scientific discovery and cannot thrive if it relies solely on industry or private interests.

Justification

As stated at the start of this manuscript:

This document is inspired by discussions on the lives and works of Jane Goodall, Charles S. Peirce, Karl Popper, Willi Hennig, and the Stoic philosophers Epictetus, Seneca, and Marcus Aurelius. It is intended as an accessible reflection for early-career researchers and students.

Why, though, should a graduate student in bioinformatics, especially one enrolled in Programming II and learning to code in Python, care about philosophy, chimpanzees, or scientific method?

Because the skills that matter most in your career (clarity of thought, intellectual courage, and principled decision-making) are not taught by syntax alone.

This manuscript weaves together lessons from science, philosophy, and history to help you reflect on why you’re coding, not just how to code. As you learn Python for bioinformatics, you’ll be writing scripts to parse genomic data, run simulations, or infer phylogenetic trees. But behind every algorithm is a reasoning process—and it matters whether that process is abductive, deductive, or inductive. It matters whether you’re blindly following popular tools or questioning their assumptions.

Through the lens of Jane Goodall, you’ll see the power of doing science that breaks conventions and tells a compelling story. From Peirce, you’ll learn how scientific inquiry unfolds through cycles of guesswork, testing, and refinement. With Popper, you’ll confront the importance of falsifiability in science. Hennig reminds us that rigor and logic must anchor even the most complex inferences. And the Stoics offer tools to face the inevitable frustrations of debugging, rejection, and long hours at the bench or terminal.

This isn’t just a side lesson. It’s a foundation. Learning to program means learning to reason. And reasoning well means understanding not only the rules of Python, but also the logic of science and the psychology of bias.

In an era of generative AI and rapidly shifting tools, students must be more than tool users—they must be thoughtful creators, able to question trends, resist hype, and think for themselves. This document invites you to slow down, reflect, and cultivate the intellectual independence that defines truly impactful scientists.

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