Questioning the Question: Why Intent Matters in Every Study.
Always ask yourself: What’s the intent of this study?
This piece explores how intent shapes research, belief, and social narratives — and why asking why matters as much as asking what.
This is an important question to revisit because time keeps teaching us that knowledge—especially about history, anthropology, and the sciences—is never static. Information about human behavior, biology, and society constantly evolves as new discoveries refine what we thought we knew. Fields such as medicine, physiology, psychology, sociology, and nutrition are always expanding. The picture of existence keeps getting updated.
Acknowledging that expansiveness requires humility. Humanity is still at the beginning of understanding itself and the universe. Each year, we learn more, and that’s why I hold the mindset that we shouldn’t deny something’s existence until we can prove it doesn’t.
Take radio waves as an example: they existed long before we invented radios to detect and use them. Similarly, we can’t categorically deny the possibility of a cosmic creator, spirits, or other unseen phenomena simply because we lack the instruments to measure them. Materialists often demand concrete proof, but absence of evidence isn’t evidence of absence—it may just mean we haven’t yet developed the tools to perceive what’s there.
We didn’t know the microscopic world existed until the invention of the microscope. We didn’t understand oxygen as a distinct element until the late 18th century, when scientists like Joseph Priestley and Antoine Lavoisier identified it. Trees don’t “separate oxygen particles” exactly, but through photosynthesis they absorb carbon dioxide, use the carbon to build tissue, and release oxygen as a by‑product—making the air cleaner and contributing to their growth.
Humans often deny what they can’t yet prove, and that skepticism has its place. It keeps inquiry grounded. At the same time, both spirituality and materialism have been misused by people seeking power or control. Whether atheist, believer, or skeptic, anyone can act harmfully—the constant variable is human behavior itself. Our desires and needs drive us, sometimes toward good, sometimes toward exploitation. That’s why frameworks like Maslow’s Hierarchy of Needs remain relevant: they remind us that our actions often stem from fundamental human motivations rather than ideology alone.
Another example: proving where emotions appear in the brain and how hormones influence bodily sensations only shows the hardware doing its job. I tend to roll my eyes when people use that argument as if it explains everything.
Think of your computer: it has hardware, but without software and a power source, it’s inert—just a block of materials. The human body works similarly. We have hardware (organs, tissues, neurons), software (the mind’s programming and learned patterns), and a power source (bioelectric energy).
Even with hardware and electricity, without the “software” that organizes signals, the body wouldn’t know how to process hormones, breathe, interpret facial expressions, or learn. A baby can read a parent’s emotions without formal teaching—that’s innate programming shaped by evolution. But when the hardware malfunctions, issues appear: glitches, delays, or breakdowns. Just like a computer, if a component fails, the system stalls or shuts down until repaired or replaced.
Our bodies operate on the same principle. Electrical impulses travel through nerves; organs communicate through chemical and neural signals. The gut, for instance, sends messages to the brain via the vagus nerve, influencing mood and cognition. When an organ fails, the system destabilizes—sometimes fatally.
Despite all we’ve learned, consciousness remains largely mysterious. Scientists have begun to understand that experiences can leave biological marks passed down through generations—a field known as epigenetics, which studies how environmental factors and trauma can influence gene expression without altering DNA itself.
We’ve advanced enough to improve human life dramatically—reducing malnutrition, disease, and injury—but some scientific pursuits still raise questions about intent. Not every dataset needs to be chased endlessly. Sometimes, the more meaningful question is why we’re studying something at all.
Let’s take divorce rates as an example.
Comparing divorce rates among heterosexual, gay, and sapphic couples often reveals more about the intent behind the study than about the people being studied. Many of these analyses are shaped by cultural or political agendas rather than genuine curiosity about human relationships.
Historically, marriage was a property‑based institution. In many societies, it functioned as a contract among wealthy or aristocratic families to consolidate status and wealth. The wife’s role was often defined by her capacity to produce heirs—an expectation that tied her body directly to property and lineage. Although marriage laws have evolved, that legacy still influences how we interpret marital data.
Divorce statistics can be misleading when used to fabricate social “problems.” A rising divorce rate isn’t necessarily negative—it can signify that people feel freer to leave relationships that no longer serve them emotionally or mentally. For women, the right to divorce without cause or a husband’s permission is historically recent, marking a major step toward autonomy.
When it comes to sapphic relationships, the data are even murkier. Official statistics rarely capture sexuality accurately; most divorce filings don’t include a checkbox for both partners’ identities. Surveys and questionnaires often rely on small, self‑selected samples, which limits their reliability. As a result, claims that sapphic couples have higher divorce rates are based on incomplete data—and frequently weaponized by political figures to reinforce narratives about instability or morality.
But if sapphic couples do separate more readily, that can be read as a positive indicator of agency. It suggests they’re less bound by patriarchal expectations to “stick it out” when a relationship becomes stagnant or unhealthy. Choosing to leave is an act of self‑respect, not failure.
That’s where bias comes into play.
We’ll get deeper into that later, but it’s worth noting that most studies begin with a theory—a guiding question that shapes the research design, participant selection, and data interpretation. The intent behind that theory often determines what gets studied and what gets ignored.
Not all participants carry equal weight in research, especially in fields touching social justice, diversity, equity, and inclusion. When studies focus on marginalized communities—say, narrowing down to school systems in the U.S. and even more specifically to school counselors—the voices of participants from the most oppressed groups become crucial. Their experiences can reveal systemic issues others overlook. Yet many decline participation, often due to distrust or fatigue from being studied rather than supported. As a result, researchers work with whoever is willing, which can skew representation.
Rigidity compounds the problem. Some prominent figures in academia become so entrenched in their frameworks that they lose touch with lived reality. Their work narrows until they can’t see the broader picture. History offers examples—Albert Einstein, for instance, was brilliant but reportedly struggled with daily life and relied on others for basic tasks. Intellectual isolation can make researchers defensive when their work is questioned.
That defensiveness shows up in modern cases too. Consider the “brain scan doctor” who claimed everyone should undergo brain imaging to tailor treatment plans. When another physician pointed out flaws—like ignoring the lack of affordable healthcare access in the U.S.—he reacted with irritation instead of reflection. The critique wasn’t about invalidating his entire theory; it was about context. His approach overlooked socioeconomic realities and seemed more like marketing for his book and supplement brand than genuine scientific inquiry.
The takeaway: good research requires humility. You must test your theory not only to prove it right but also to prove it wrong. Without that balance, studies risk becoming echo chambers for personal bias rather than tools for understanding.
Capitalism fuels many pursuits—and the prestige of being known for something.
You can often trace a researcher’s or influencer’s motives by looking at the brands funding their work. Industries have long shaped narratives to protect profit: the meat industry promotes red meat as essential and “bioavailable,” the tobacco industry once funded studies denying links between smoking and cancer, and food corporations push the idea that ultra‑processed foods are harmless if you just “balance calories in and calories out.” These campaigns distract from deeper truths—how hormones, stress, and overwork affect health—and why metrics like BMI fail to measure well‑being.
Capitalism thrives on keeping people overworked and under‑rested, because illness and poverty sustain consumption. When studies focus on declining birth rates, divorce rates, or the so‑called “loneliness epidemic,” they often frame these as crises rather than symptoms of patriarchy, capitalism, and religious dogma. A lower birth rate isn’t inherently bad—it can reflect women reclaiming autonomy and rejecting childbearing as social currency. The child‑free‑by‑choice movement is a sign of agency, not decline. Everyone’s choice deserves respect, whether rooted in physiology, preference, or circumstance.
Those who panic about falling birth rates often fear losing access to bodies—fewer people mean fewer consumers, fewer workers, and less exploitation. Capitalism depends on constant replenishment of labor and markets; when that slows, power at the top feels threatened.
Now consider studies on Intimate Partner Violence (IPV) that break data down by sexual orientation—lesbian, gay, heterosexual, bisexual. When misread or weaponized, these studies become tools of stigma. One widely circulated study, for instance, measured who experienced IPV, not who perpetrated it, yet commentators twisted it to claim “lesbians are violent.” That distortion ignores context: many lesbians have had relationships with men, and IPV can occur in any gender configuration.
Yes, sapphic couples can experience abuse—women are not exempt from harmful behavior—but the intent of such studies matters. Are they seeking solutions or reinforcing stereotypes? The people who misuse these findings often aim to control women’s bodies and relationships, discouraging women from loving other women. Historically, lesbians have threatened patriarchy precisely because they decenter men entirely. Their focus—our focus—is on women’s well‑being, autonomy, and solidarity.
If this study focused on history rather than gender, it would reveal another gap: men often don’t report being victims of intimate partner violence (IPV). The numbers for gay men should be much higher. Many men—gay or straight—avoid reporting sexual assault or other forms of abuse because of cultural expectations around masculinity. They fear ridicule or disbelief.
Even when men do participate in IPV questionnaires, honesty can be complicated. Would they recognize verbal, emotional, or psychological abuse as violence? Often not. Many people don’t realize they’re being mistreated until someone helps them name it.
Men also rarely speak about being harassed or stalked by women. Social norms trivialize their discomfort—other men might joke that he should “take the offer.” I once had a coworker confide in me about a woman’s persistent, inappropriate behavior at his job. He needed someone to listen because it made his work environment unbearable. That silence around male victimhood shows how toxic our social infrastructure has become.
A lot of people treat others poorly, feel entitled to access their bodies or emotions, and repress anger until it manifests as control or violence. Women can do the same; abuse isn’t gender‑exclusive. But when researchers design studies, intent matters. Biases shape what gets measured and what gets ignored.
History is full of examples. For decades, anthropology taught the “man the hunter, woman the gatherer” model—a misconception born from male bias. Even the old evolutionary chart showing a monkey turning into a man oversimplified human origins. We now know there were multiple hominin species, and evidence shows that roughly 40–50 percent of prehistoric women hunted as well. Modern technology confirmed what earlier evidence already suggested but was dismissed.
The same happened with wolves: early researchers assumed strict hierarchies based on captive observations, but later field studies revealed that wild wolf packs are family units, not dominance‑based structures. These examples show how easily bias distorts research.
That’s why asking about intent is essential. Every study should be approached with discernment—questioning not just what it claims, but why it was done and who benefits from its conclusions.