Nutritional Science Started from the Wrong Question
Abstract
Traditional nutrition relies on observational studies (people misreport intake), epidemiology (correlations aren't causation), and short trials (weeks, not decades). Every five years, the guidelines shift. This essay uses the methodology of harder sciences: start with physical and biochemical laws that don't change, then work through material evidence—isotopes in ancient bones, archaeological remains, metabolic pathways identical across all humans.
One biochemical limit (the protein ceiling) plus isotopic data from 2 million years of fossils reveals what humans are actually adapted to eat. This is deductive reasoning from immutable constraints, not statistical inference from imperfect surveys. The difference in reliability isn't subtle.
Why You Should Keep Reading
Most practitioners hide their actual methodology until you're already paying them. We're doing the opposite.
These seven principles are the filter for every decision we make—whether interpreting your labs, teaching you breath regulation, or working through an emotional block. If you read them and think "this makes sense," the work will make sense. If they feel off, we're probably not aligned.
Here's what makes this worth your time: these principles prevent a specific category of problem—the kind created by the helping process itself. Expert dependency that never resolves. Metric obsession that replaces felt experience. Symptom management that ignores underlying blocks.
You've likely experienced at least one of these. That's why you're reading.
The framework won't eliminate all challenges, but it will eliminate the ones caused by following advice that was never designed to set you free.
What if nutrition science started from the wrong question?
For decades, we've asked: "What should humans eat?"
The better question: "What can humans eat?"
The difference isn't semantic. One approach generates observational studies where participants misreport their intake by 20-50%. It produces controlled trials lasting weeks when diseases develop over decades. It yields dietary guidelines that contradict themselves every five years, then wonders why nobody trusts nutrition science.
The other approach uses the methodology of harder sciences. Start with physical constraints that don't change—biochemical limits identical across all humans, thermodynamic laws measurable in any laboratory, isotopic signatures in bones that can't misreport their diet. Then reason forward from there.
This essay demonstrates that second method. No surveys. No epidemiological correlations mistaken for causation. Just protein ceilings, energy density laws, and 2 million years of evidence from human fossils.
When you begin with what's mechanistically impossible, what remains reveals what humans are actually adapted to eat.
I. The Problem We're Not Solving
The scene repeats in millions of offices. A patient receives dietary advice, follows it carefully, returns six months later to find the problem unchanged or worse. Not because doctors are incompetent or patients undisciplined, but because the entire system works from the wrong map.
The current approach to nutrition resembles medieval astronomy: elaborate epicycles added to a fundamentally incorrect model. We conduct observational studies knowing participants misreport intake by 20-50%. We run controlled trials for weeks when diseases develop over decades. We update guidelines that contradict themselves every five years, then wonder why nobody trusts nutrition science.
But we already have a better method. We just haven't used it consistently.
How This Connects to HUC Principles
This essay demonstrates "explainable mechanisms over unverifiable belief" in action.
Rather than relying on observational studies or epidemiological correlations, we start with biochemical constraints that operate regardless of preference or belief. The protein ceiling exists whether you're vegan, paleo, or carnivore. Energy density follows thermodynamic laws. The Randle cycle describes fuel metabolism with mechanisms observable in any laboratory.
When we combine these immutable constraints with archaeological evidence—isotopes in ancient bones that can't misreport their diet—we can reason deductively about what humans are physiologically adapted to eat.
This is the approach: identify what doesn't change first, then work forward from there.
II. What Actually Constrains a Diet
Before asking "what should humans eat," ask: "what can humans eat?"
The Protein Ceiling
Start with a hard limit, one that operates regardless of culture, preference, or dietary philosophy.
Feed someone nothing but lean rabbit meat. Within days, they'll develop headaches, diarrhea, nausea. Within weeks, they'll die. This isn't food poisoning or allergy. It's protein toxicity, known colloquially as "rabbit starvation."
The mechanism is straightforward: protein metabolism generates ammonia. The liver converts ammonia to urea for excretion. This system has capacity limits. Push beyond roughly 35-40% of calories from protein, and ammonia accumulates faster than the liver can clear it. The result is hyperammonemia, with symptoms ranging from discomfort to death.
This isn't theoretical. Arctic explorers documented it. Vilhjalmur Stefansson, who lived among the Inuit, described parties of men dying surrounded by fresh game, purely from eating too much lean meat. The Inuit themselves knew this. They prioritized fatty organs and discarded lean muscle for their dogs.
The implication is simple: if your ancestors survived primarily on animal foods, they needed fat. Not as a preference. As biochemical necessity.
This ceiling sits there, undeniable, rarely mentioned in dietary debates. It eliminates entire possibility spaces. No hunter-gatherer could thrive on 60% protein. No Paleolithic human could survive on lean game alone.
So when isotope data shows our ancestors at apex predator trophic levels (consuming large quantities of animal foods), we can deduce the macronutrient distribution without dietary records. High animal intake + protein ceiling = fat-centric diet.
The Energy Equation
Now consider the other constraint: energy density.
Carbohydrates provide 4 calories per gram. Fat provides 9. This isn't opinion or trend. It's thermodynamic reality, measurable in a bomb calorimeter.
Side note: It is true that we do not actually "burn" calories. We are not, in fact, a bomb calorimeter. Nor is the simple measure of calories-in and calories-out a comprehensive measure of energy processing (pin that thought for later). However, we do "bioprocess" food in order to survive. Burning calories is a reliable, albeit incomplete, measure of the amount of food we need to eat.
For a Paleolithic human expending 2,500-3,000 calories daily through hunting, foraging, and survival, this difference matters. Carrying capacity matters. Processing time matters. Return on effort matters.
A kilogram of beef fat yields 9,000 calories. A kilogram of tubers yields roughly 800. To obtain equivalent energy from plants requires harvesting, carrying, and often processing 11 times the mass.
This doesn't make plant foods worthless. They provide nutrients, variety, and resilience during scarcity. But it does explain why, when available, fatty animal foods would be prioritized. Not from some mystical ancestral wisdom, but from basic energetic logic.
The Metabolic Switch
The human body operates two primary metabolic modes, governed by the Randle cycle.
In glucose metabolism, insulin rises, signaling cells to burn sugar and store fat. In fat metabolism, insulin stays low, and cells preferentially oxidize fatty acids and ketones.
These modes compete. High glucose availability suppresses fat oxidation. High fat availability suppresses glucose oxidation.
This isn't a design flaw. It's efficiency. The body selects the most available fuel and downregulates the other pathway to avoid metabolic interference.
But here's the interesting part: unlike most mammals, humans maintain robust ketogenic capacity. We can generate ketones sufficient to supply 60-70% of brain energy, something most animals cannot do efficiently.
Why would natural selection preserve expensive metabolic machinery unless it saw regular use?
The simplest explanation: our ancestors routinely operated in fat metabolism mode. Not occasionally during famine, but as a default state punctuated by carbohydrate availability.
III. What the Dead Tell Us
Bones don't lie, but they also don't speak plainly. We must learn their language.
Reading Isotopes
When an animal eats, stable isotopes from its food incorporate into its tissues. Different food sources have characteristic isotopic signatures. By analyzing bone collagen or tooth enamel, we can reconstruct diet decades or centuries after death.
Two isotopes prove particularly useful:
δ¹⁵N (nitrogen-15): Each trophic level up the food chain enriches nitrogen-15 by approximately 3-4‰ (parts per thousand). A δ¹⁵N value of 6‰ suggests herbivore. 9-10‰ suggests omnivore or secondary consumer. 12-14‰ suggests apex predator.
δ¹³C (carbon-13): Plants use two primary photosynthetic pathways: C3 (most trees, tubers, temperate grasses) and C4 (tropical grasses, some sedges). These pathways discriminate differently against carbon-13, creating distinct signatures. Marine foods also show characteristic values.
Together, these isotopes reveal not just what someone ate, but their position in the ecosystem.
What We Find
At Olduvai Gorge, Tanzania, Homo habilis remains from 2-3 million years ago show δ¹⁵N values of 8-10‰. Not herbivore values. Not even typical omnivore values. These are the signatures of animals consuming substantial quantities of other animals.
Accompanying stone tools show characteristic percussion marks: specifically, the type of controlled fracturing used to extract marrow from long bones.
Why marrow specifically? Because it's 70-80% fat, providing 9 calories per gram in a neat, packageable form. Early humans weren't just hunting. They were targeting the fattiest tissues available.
Move forward to Neanderthals. Shanidar Cave, Iraq, 70,000 years ago: δ¹⁵N values of 10-12‰. Apex predator levels. But dental calculus (fossilized plaque) preserves plant microfossils showing cooked grains and tubers.
So Neanderthals ate plants. But their isotopic signature indicates the bulk of their protein (and therefore, given the protein ceiling, their calories) came from animals. Specifically, from fatty animals like bison and aurochs.
At Vanguard Cave, Gibraltar, Neanderthal remains show even higher δ¹⁵N (12-14‰) with distinctive δ¹³C values indicating marine foods. These Neanderthals ate seals and large fish: some of the fattiest animals available.
Skip to Upper Paleolithic Homo sapiens at El Mirón, Spain (50-10,000 years ago): δ¹⁵N of 9-11‰, with evidence of increased plant processing tools. Still high animal intake, but with more sophisticated plant use.
Then the Neolithic. At Çatalhöyük, Turkey (10-5,000 years ago), δ¹³C values shift toward C4 plants (cereals). δ¹⁵N drops to 8-10‰. Still substantial animal intake, but noticeably less than Paleolithic populations.
A pattern emerges across continents and climates: apex predator trophic levels for 2 million years, then a gradual shift downward coinciding with agriculture.
What the Bones Show
Isotopes tell us what people ate. Skeletons tell us how they fared.
Paleolithic skeletons show robust bone density, low dental caries, and minimal degenerative joint disease (at least among those who survived childhood and trauma). The Shanidar 1 Neanderthal lived to approximately 40-50 years despite severe injuries, showing bone remodeling and healing that indicates good nutrition.
Early Neolithic skeletons show increased dental wear from grinding grains, more caries from increased carbohydrates, and the first signs of deficiency diseases. Average height decreases. This doesn't mean agriculture was purely negative. It allowed population growth and civilization. But it represents a nutritional trade-off.
Modern hunter-gatherers provide living evidence. The Hadza of Tanzania show cardiovascular markers superior to industrial populations. The Inuit, consuming 70-80% calories from fat (primarily seal blubber and fatty fish), historically showed low rates of heart disease and diabetes until Western diets arrived.
IV. The Exceptions That Prove the Rule
A rigorous framework must account for variation, not just central tendency.
Marine Adaptations
At Pinnacle Point, South Africa, 164,000 years ago, shell middens reveal systematic exploitation of coastal resources. These populations accessed a different fat source: fish oils rich in omega-3 fatty acids, seal blubber, and shellfish.
Their isotopic signatures differ from terrestrial hunters, but they share a pattern: prioritization of the fattiest available foods. When you live by the sea, that means marine mammals and oily fish.
Plant-Heavy Populations
Paranthropus boisei, the "Nutcracker Man" (not our direct ancestor, but a contemporary hominin), shows δ¹³C values of -14 to -12‰, indicating heavy C4 plant consumption, likely from sedges and grasses.
But notice: this represents a different evolutionary path. Paranthropus developed massive jaws and enormous grinding teeth. Homo developed larger brains and smaller guts. These are distinct adaptations to distinct diets.
Within the Homo lineage, plant use varied by region. Gesher Benot Ya'aqov, Israel (780,000 years ago) shows extensive tuber processing: the earliest clear evidence of plant food emphasis. Some Paleolithic populations in forested regions likely consumed more plant foods than grassland hunters.
But even in these cases, animal foods provided the protein backbone. And given the protein ceiling, that necessitated substantial fat intake.
Seasonal Variation
At Dolní Věstonice, Czech Republic (30,000 years ago), archaeologists found evidence of seasonal dietary shifts. Summer: increased nut and plant remains. Winter: almost exclusive reliance on mammoth and reindeer, meaning heavy fat consumption when plant foods became unavailable.
This reveals something fundamental: humans show metabolic flexibility, the ability to thrive on different fuel ratios, but within constraints. You can't eat 60% protein. You need either fat or carbohydrates as primary fuel. The evidence suggests our ancestors regularly used both, but relied on fat more consistently.
V. The Modern Mismatch
If ancestral diets were fat-centric with variable plant intake, why does modern nutritional advice emphasize the opposite?
The Diet-Heart Hypothesis
In 1961, Ancel Keys published his Seven Countries Study, showing correlation between saturated fat intake and heart disease. This became the foundation for decades of low-fat dietary recommendations.
But Keys' study had problems. He selected 7 countries from 22 available, excluding those that didn't fit his hypothesis. France, with high saturated fat intake and low heart disease, wasn't included. Neither was Switzerland.
Follow-up studies told a more complex story. The 2010 meta-analysis by Siri-Tarino et al., examining 21 studies with 347,747 participants, found: "There is no significant evidence for concluding that dietary saturated fat is associated with an increased risk of CHD or CVD."
The 2024 meta-analyses go further, distinguishing between saturated fat from whole foods (meat, dairy, eggs) versus processed sources (hydrogenated oils, processed meats). The former shows neutral or beneficial effects on cardiovascular markers when carbohydrates are reduced. The latter remains problematic.
The Real Culprit
Metabolic syndrome (the cluster of conditions including insulin resistance, obesity, high triglycerides, and hypertension) affects roughly a third of American adults. Its rise parallels not increased fat consumption, but increased refined carbohydrate and seed oil consumption.
Between 1961 and 2011, US dietary fat intake decreased from 45% to 34% of calories. Carbohydrate intake increased from 39% to 51%. Obesity rates tripled.
This correlation doesn't prove causation. But it raises questions about whether we've been fighting the right enemy.
The Randle Cycle Revisited
Return to metabolic first principles. The Randle cycle describes how glucose and fatty acids compete for oxidation.
In a low-carb, high-fat diet, cells primarily burn fat. Insulin stays low. Fat oxidation runs efficiently.
In a low-fat, high-carb diet, cells primarily burn glucose. Insulin rises after meals but clears between them. This works fine if you're insulin sensitive.
But in a high-fat, high-carb diet, you create metabolic confusion. Insulin rises from carbohydrates, signaling fat storage. But dietary fat provides a substrate for that storage. The result: efficient fat accumulation, poor fat oxidation, rising triglycerides, insulin resistance.
This is the modern Western diet. Neither fish nor fowl, neither the high-fat pattern humans evolved eating nor the high-carb pattern some agricultural societies adapted to. It's metabolically incoherent.
VI. Individual Variation
The ancestral pattern provides a template, not a prescription. Genetic variation matters.
Lactase Persistence
Most mammals lose the ability to digest lactose after weaning. Most humans do too, except populations with pastoral ancestry.
A mutation in the MCM6 gene, arising roughly 10,000 years ago in northern Europe and independently in East Africa, allows lactase production to continue into adulthood. Today, about 35% of humans retain this ability.
This represents rapid evolutionary adaptation to a new food source. For those with the mutation, dairy provides a valuable source of fat and protein. For those without, it causes digestive distress.
AMY1 Copy Number
Humans show variable copies of the AMY1 gene, which produces salivary amylase for starch digestion. Populations with long agricultural histories (East Asians, Europeans) average 6-7 copies. Populations with recent agricultural adoption (pastoralists, some hunter-gatherers) average 4-5 copies.
Higher copy number enables more efficient starch digestion. People with fewer copies may experience more rapid blood sugar spikes from starchy foods, suggesting they'd fare better on lower-carbohydrate approaches.
APOE and Fat Metabolism
The APOE gene comes in three common variants: E2, E3, E4. E3 is most common. E4, present in roughly 25% of people, increases Alzheimer's risk and alters cholesterol response to dietary fat.
E4 carriers may need to emphasize unsaturated fats over saturated fats, particularly in the context of high total fat intake. This doesn't invalidate the ancestral framework, but it requires individual calibration.
The Microbiome
Your gut bacteria determine how you extract nutrients from food. Some people's microbiomes efficiently harvest energy from fiber. Others don't.
The microbiome adapts to diet over weeks to months. This means dietary experiments need adequate time to assess true response. Not days, but 4-6 weeks minimum.
VII. Practical Translation
How do you translate evolutionary and biochemical evidence into daily meals?
The Framework
Base Layer (40-70% of calories from fat)
Prioritize whole-food sources:
Fatty cuts of meat (ribeye, pork shoulder, lamb)
Fatty fish (salmon, mackerel, sardines)
Whole eggs
Avocados
Nuts and seeds
Extra virgin olive oil
The specific percentage depends on carbohydrate intake. If you're consuming 20-30% carbohydrates, aim toward 50-60% fat. If you're consuming 10% carbohydrates, you can go higher on fat (60-70%) while keeping protein moderate.
Middle Layer (20-30% of calories from protein, or 1.2-2.0 g/kg body weight)
Whole cuts of meat (including organs)
Fish and shellfish
Eggs
If tolerated: dairy
Note the protein ceiling. A 70kg person eating 2000 calories needs roughly 120-140g protein (480-560 calories). More isn't necessarily better and can cause metabolic stress.
Top Layer (10-30% of calories from carbohydrates)
Non-starchy vegetables (unlimited)
Tubers (sweet potatoes, regular potatoes, cassava)
Fruits (especially berries)
Nuts
For those with high AMY1 or high activity: properly prepared grains
Processing matters. Cooking denatures lectins. Soaking and fermenting reduce phytates. Sprouting increases nutrient availability.
What to Minimize
Refined grains and sugars
Seed oils high in omega-6 (soybean, corn, cottonseed)
Processed meats with additives
The combination of high fat plus high refined carbohydrates
Sample Day
Breakfast: Three eggs scrambled in butter with spinach, half an avocado 500 calories, 42g fat, 24g protein, 8g net carbs
Lunch: Salmon (6oz) with olive oil, roasted Brussels sprouts 450 calories, 28g fat, 40g protein, 12g net carbs
Dinner: Grass-fed ribeye (8oz), roasted sweet potato, side salad with olive oil 800 calories, 52g fat, 60g protein, 30g net carbs
Snack: Handful of macadamia nuts 200 calories, 21g fat, 2g protein, 4g net carbs
Total: ~2000 calories, 65% fat, 25% protein, 10% net carbs
This resembles isotopic evidence from Paleolithic populations while being achievable with modern foods.
Personalization
If you have high AMY1 (agricultural ancestry): Increase carbohydrates to 20-30%, reduce fat to 50-60%. Include properly prepared grains like rice or oats.
If you have lactase persistence: Dairy products become valuable. Full-fat yogurt, cheese, butter from grass-fed sources.
If you have APOE4: Emphasize fish and olive oil over red meat. Include more plant foods.
If you're pregnant or lactating: Increase overall calories by 300-500. Prioritize DHA-rich fish, iron-rich organ meats. Aim for 1.5g protein per kg body weight.
If you're an athlete: Increase protein slightly (toward 2.0g/kg) and add strategic carbohydrates around training.
If you're trying to reverse metabolic syndrome: Start with 60-70% fat, 10% carbs, monitor fasting glucose and triglycerides. Expect metabolic adaptation over 4-8 weeks.
Monitoring
Track biomarkers every 3-6 months:
Fasting glucose and HbA1c
Lipid panel (with particle size if available)
CRP for inflammation
Vitamin D
Homocysteine
Iron status (especially for women)
Use how you feel as primary guidance:
Energy stable throughout the day?
Mental clarity?
Sleep quality?
Hunger signals normal?
Digestive comfort?
The optimal diet makes you feel good, not just test good. But testing catches problems before symptoms appear.
The Self-Verification Loop
The HUC framework emphasizes that your direct experience matters more than any practitioner's interpretation of your labs. Track biomarkers to catch problems early, but use felt experience as primary guidance.
This means:
If labs look great but you feel terrible → something's wrong with the approach, even if the numbers say otherwise
If labs show "suboptimal" ranges but you feel amazing → your optimal may differ from population averages
If both labs and experience improve together → you've found something mechanistically real
The body doesn't lie about what's working. The same principle that lets us read isotopes in ancient bones applies to reading signals in your own physiology. You just need to learn the language.
This is self-verification in action. Not blind faith in data. Not dismissal of measurement. But recognition that the ultimate test is whether you're building clarity, energy, and health—things you can feel directly.
Why emphasize female reproduction in the optimal diet definition?
Male reproductive capacity extends decades longer, making it less nutritionally sensitive. Female fertility requires adequate body fat (typically 20-25%), specific micronutrients (iron, folate), and high energy availability. These demands shaped food-seeking behavior more strongly than male reproduction. This doesn't mean the diet is only for women. It means female constraints were evolutionarily stricter.
Don't observational studies show plant-based diets reduce disease?
They show correlation, often confounded by lifestyle factors (plant-based dieters often exercise more, smoke less, etc.). The mechanistic evidence presented here examines causation. This framework includes substantial plant intake, just not as the primary calorie source.
What about environmental sustainability?
Valid concern, outside this paper's scope of physiological optimization. The solution isn't abandoning animal foods but sourcing them sustainably: regenerative grazing, reduced food waste, appropriate portions. A 6-8oz serving of meat per day with nose-to-tail use is vastly different from industrial factory farming.
Didn't Paleolithic people only live to 30?
High infant mortality and trauma skew averages. Among those who survived childhood and avoided accidents, living to 50-60 was common. More to the point, how they lived matters. Robust health until death, not decades of chronic disease.
Can't I just take supplements to make a plant-based diet equivalent?
You can approximate. But bioavailability differs. Heme iron absorbs better than non-heme, preformed vitamin A better than carotenes, EPA/DHA better than ALA. You're working against your physiology rather than with it. Possible? Yes. Optimal? The evidence suggests not.
IX. The Weight of Evidence
Let's trace the logical chain:
Biochemical constraint: Humans cannot survive on >40% protein calories.
Energetic constraint: Fat provides 9 kcal/g vs. carbohydrates' 4 kcal/g.
Isotopic evidence: Paleolithic humans show apex predator δ¹⁵N values (9-12‰) indicating high animal food consumption.
Mathematical deduction: High animal intake + protein ceiling = fat-centric diet (40-70% of calories).
Metabolic evidence: Robust ketogenic capacity suggests regular fat metabolism.
Archaeological evidence: Systematic marrow extraction, exploitation of fatty animals.
Skeletal evidence: Paleolithic populations show robust health markers.
Modern analogs: Hunter-gatherers and ketogenic studies confirm metabolic viability.
Mechanistic coherence: Randle cycle and insulin dynamics explain modern disease patterns as mismatches.
Genetic variation: Recent adaptations (lactase, AMY1) show evolution occurring but not complete transformation.
Each piece of evidence independently suggests fat-centric eating. Together, they form a coherent picture.
The alternative (that humans are primarily adapted to carbohydrate-based diets) requires explaining away isotopic data, dismissing the protein ceiling, ignoring energetic constraints, and attributing modern metabolic disease to factors other than dietary mismatch.
Occam's Razor favors the simpler explanation.
X. The Path Forward
This framework doesn't prescribe religious adherence to macronutrient ratios. It provides a physiologically grounded starting point, then acknowledges variation.
For most people, most of the time, a diet emphasizing whole foods with 40-70% fat from animal and whole plant sources, 20-30% protein, and 10-30% carbohydrates from vegetables, tubers, and fruits aligns with:
What we can deduce about ancestral eating patterns
What biochemistry constrains as viable
What modern metabolic evidence suggests prevents disease
What genetic variation requires for personalization
It's not about living in a cave or fetishizing the past. It's about recognizing that rapid environmental change (agricultural, then industrial) outpaced genetic adaptation, creating physiological mismatches that manifest as chronic disease.
The question isn't "What did Paleolithic people eat?" but rather "What were humans eating during the 2+ million years that shaped our metabolic machinery?"
The answer appears to be: predominantly fat and protein from animals, supplemented with variable plant foods based on availability and season. Not exclusively. Not universally. But predominantly, for long enough that our physiology reflects this pattern.
Modern health might not require perfect adherence to this pattern. But it probably requires something closer to it than what most people currently eat.
Return to Principles
This essay demonstrates one HUC principle in depth—explainable mechanisms over unverifiable belief. But the same approach applies to every aspect of health work, whether physiological or psychological.
When examining gut dysbiosis, we don't just prescribe probiotics and hope. We look at what's mechanistically blocking microbial balance—opportunistic bacteria, low stomach acid, circadian disruption—then address those constraints. When working with emotional processing through Mind Shifting, we don't rely on unverifiable energy healing. We use the direct, felt experience of emotional resistance dissolving, something clients can verify without faith.
Starting with constraints rather than recommendations creates a different kind of trust. Not trust in a practitioner's authority or a dietary ideology, but trust in mechanisms that operate independently of belief. When something works, you understand why. When something doesn't work, you have the literacy to adjust rather than abandon the entire approach.
This is what the HUC framework offers: a consistent set of filters that work the same whether you're interpreting a stool test or processing a limiting belief. The principles don't shift. The mechanisms don't require faith. The verification comes from your own experience.
For the complete framework and how these principles intersect, see The HUC Principles.
The evidence doesn't dictate your choices. It informs them.
What you do with that information remains yours to decide.
References
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Richards MP, Trinkaus E. (2009). Isotopic evidence for the diets of European Neanderthals and early modern humans. PNAS, 106(38), 16034-16039.
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