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Thirteen Phenomena Conventional Models Cannot Adequately Explain

A literature review of simultaneous trends that require separate explanations — unless they share a single biological cause

Otto Juote·MSc LSE·31 août 2026·25 min de lecture

In the modern world, a set of simultaneous trends are underway that conventional explanatory models — economics, sociology, psychology, epidemiology — treat as SEPARATE phenomena, each with its own explanation. BERM's civilization model proposes that these are different manifestations of the SAME biological cascade: EMF → VGCC/CRY → Ca²⁺ → hormones/neurotransmitters → behavior/disease.

Below are 13 phenomena where the conventional explanation is either incomplete, contradictory, or unable to explain cross-species synchrony.

01The Klimentidis Paradox: 8 Species Are Getting Fatter

Klimentidis et al. 2011 (Proc. R. Soc. B): 24 populations of 8 species — primates, rodents, dogs, cats — whose weight trajectories were examined over decades. EVERY population's weight trend was positive (p = 1.2 × 10⁻⁷).

Replication status: The study has NOT been replicated (179 citations, 0 replications, LessWrong 2023). The weight gain in NTP control rats is PARTIALLY explained by changes in control diet composition over time. Weight gain in livestock and pets is partially explained by changes in feeding. BUT: data from research colony primates (macaques, chimpanzees, marmosets) under controlled conditions and wild rat data remain unexplained.

Conventional explanation

No comprehensive explanation. Proposed candidates (obesogens, microbiome changes) fail to explain weight gain in research primates or wild rats.

BERM explanation

EMF → VGCC → Ca²⁺ → disruption of pancreatic β-cell insulin secretion (VK46) + melatonin↓ → circadian metabolic disruption. The same environmental change (rising EMF background in research facilities and urban environments) affects all species simultaneously.

Epistemic level:L* (primates + wild rats M|C, overall requires replication)

Sources: Klimentidis et al. 2011 Proc R Soc B 278:1626–1632; LessWrong replication analysis 2023; Brown et al. 2016 Obes Res Clin Pract 10:243–255

02Negative Flynn Effect: IQ Is Declining in Developed Countries

Bratsberg & Rogeberg 2018 (PNAS, N=730,000): IQ rose in cohorts born 1962–1975 and FELL in cohorts born 1975–1991 in Norway. The same decline has been reported in Denmark, Finland, France, the Netherlands, Britain, and Australia. The decline is 5–7 points per generation since the mid-1990s.

USA data (Dworak et al. 2023, Intelligence, N=394,378): three cognitive domains declined 2006–2018 (verbal reasoning, matrix reasoning, letter-number sequences), but 3D spatial rotation ROSE. This dissociation is informative: the declining domains involve prefrontal cortex abstract reasoning, while the rising domain involves parieto-occipital spatial processing.

Conventional explanation

Bratsberg & Rogeberg demonstrated with SIBLING COMPARISON (within-family) that the decline is environmental, NOT genetic. Which environmental change? "Debated — shifts in schooling, media use, or attention have all been proposed" (Cogn-IQ 2026). No consensus.

BERM explanation

EMF → BDNF↓ (VK23: Cav1.2 → CREB → BDNF transcription↓) + melatonin↓ → sleep↓ → cognitive consolidation↓. BDNF is the key molecule of neuroplasticity, and its decline affects the prefrontal cortex (abstract reasoning) more than parieto-occipital regions (spatial).

This explains the Dworak 2023 dissociation: abstract reasoning↓ but spatial↑ (video games compensate for spatial). The conventional "screen time" explanation would predict ALL cognitive functions declining — no dissociation should exist.

Timing: The decline begins in the 1990s = 2G networks, PCs, fluorescent lighting become widespread. Sibling comparison rules out genetics → ENVIRONMENTAL CHANGE → BERM identifies it.

Epistemic level:M|C (strong epidemiological + mechanistic logic)

Sources: Bratsberg & Rogeberg 2018 PNAS 115:6674–6678; Dworak et al. 2023 Intelligence 101:101793; Flynn & Shayer 2018

03"Deaths of Despair": Mortality from Despair

Case & Deaton 2015/2020: mortality from overdoses, alcoholic liver disease, and suicide has risen 56–387% by age cohort over the last 20 years in the USA. Particularly middle-aged men without college education. Life expectancy FELL — for the first time during peacetime in an industrialized country.

Conventional explanation

Socioeconomic: deindustrialization, wage stagnation, opioid overprescription. Case & Deaton describe it as "cumulative disadvantage." BUT: (a) in Europe, the same socioeconomic factors exist WITHOUT a comparable mortality rise, (b) why SPECIFICALLY middle-aged men, (c) a PNAS 2024 reevaluation shows that "despair" per se does not explain racial heterogeneity.

BERM explanation

Cumulative biological cascade: T↓ 1.2%/yr: in middle-aged men, T is already naturally lower → EMF cascade pushes BELOW critical threshold → DA↓ → anhedonia → compensation with substances (opioids, alcohol) → cortisol↑ → chronic stress → pain sensitivity↑ (VK30: α2δ-1↑) → melatonin↓ → sleep↓ → depression → suicidal behavior → OXT↓ → social isolation → "despair".

Why men: T decline affects men more because absolute T levels are higher → greater absolute decline. Why USA > Europe: US EMF infrastructure is OLDER (electrification from 1890) and MORE INTENSIVE (larger houses, more devices, longer phone usage).

Epistemic level:M|C

Sources: Case & Deaton 2015 PNAS 112:15078–15083; Case & Deaton 2020 Deaths of Despair (Princeton UP); PNAS 2024 reevaluation

04The Female Happiness Paradox

Stevenson & Wolfers 2009 (AEJ:EP): women's subjective happiness has declined both absolutely and relative to men since the 1970s despite significant improvements in women's objective status. Blanchflower & Bryson 2024 (J Pop Econ): the paradox is "extremely robust" especially for negative affect: women report MORE depression, stress, and anxiety than men ALWAYS and EVERYWHERE. Science Advances 2026: two paradoxes identified — women's happiness is higher but their negative affect is ALSO higher.

Conventional explanation

Unclear. Proposals: role overload, raised expectations, measurement artifacts. None explains the TEMPORAL trend (1970→) or UNIVERSALITY (same in all countries).

BERM explanation

Women's hormonal system is more sensitive to EMF at several points: estrogen modulates VGCC expression (estrogen → Cav1.2↑); the menstrual cycle requires precise Ca²⁺ oscillation; the OXT system is MORE CENTRAL to women's social wellbeing; women are more sensitive to circadian disruption (seasonal depression 2–3× more common in women).

Epistemic level:M|C

Sources: Stevenson & Wolfers 2009 AEJ:EP 1:190–225; Blanchflower & Bryson 2024 J Pop Econ 37:16; Science Advances 2026

05The Autoimmune Epidemic

Global age-standardized prevalence nearly DOUBLED from 1990 to 2021 (GBD 2021). Celiac disease: 5-fold increase over 30 years in the USA (doubles every 15 years). MS: +30% globally 2013–2022. IBD: +46% 2006–2021. T1D nearly doubled over 40 years. Particularly CHILDHOOD T1D and IBD are rising fastest.

Conventional explanation

"Hygiene hypothesis" explains part of it. BUT: hygiene levels have not changed significantly from 1990–2021, and in children the growth is FASTEST — the hygiene hypothesis does not explain the acceleration.

BERM explanation

EMF → VGCC → Ca²⁺ → NADPH oxidase → ROS → NF-κB → proinflammatory cytokines. ADDITIONALLY: melatonin↓ → immunomodulation↓ + vitamin D↓ → T-reg function↓. Three independent EMF pathways converge on the same outcome. Children's particular vulnerability: prenatal developmental windows (VK5a).

Epistemic level:M|C

Sources: GBD 2021; NHC 2025; NCBI Bookshelf NBK605881 (2022)

06The Myopia Pandemic

Myopia prevalence rose from 10–20% to over 90% in East Asian cities in 50 years. Globally: 24.3% (1990) → 35.8% (2023), projected 39%+ (2050) — 5 billion people. Genetic change is too slow to explain the pace. COVID-19 WORSENED myopia in children (JAMA Ophthalmol 2021).

NEI 2025 (Chiang): "Despite major research investments, the interplay between genetic and environmental influences remains unclear." Lisa Ostrin (Houston): red light therapy has "shown excellent efficacy in controlling myopia progression." Identified risk factor: "use of LED lamps for homework" (BMC Ophthalmol 2020).

Conventional explanation

Near work + reduced time outdoors. BUT: (a) near work has been done for centuries — why the acceleration from 1990→, (b) red light therapy WORKS — why, (c) LED lamp use identified as a risk factor but the mechanism is unclear.

BERM explanation

Retinal dopamine regulates axial growth. DA↓ → axial elongation↑ → myopia. EMF → DA↓ (VK53, pathway D). LED lighting: blue-light dominant → melatonin↓ → dopaminergic circadian regulation disrupted. Red light WORKS because it (a) stimulates mitochondria, (b) does NOT suppress melatonin → dopaminergic recovery. LED being identified as a risk factor is DIRECT support: the LED frequency spectrum (blue peak + IF emissions) disrupts the melatonin→DA pathway.

Epistemic level:M|C

Sources: Holden et al. 2016 Ophthalmology 123:1036–1042; NEI 2025 Chiang; Wang et al. 2021 JAMA Ophthalmol 139:293–300

07Systematic Failure of Pronatalist Policy

EVERY developed country that has attempted to raise fertility through financial incentives has FAILED. South Korea: $200B+, TFR 1.08→0.72 (fell DURING the intervention period). Hungary: modest rise 1.23→~1.5. Singapore, Japan: no effect.

Conventional explanation

Incomplete. If fertility is a rational choice, sufficient financial incentives should reverse it. South Korea's $200B amounts to approximately $50,000 per family. Why isn't that enough?

BERM explanation

Quadruple lock theory: T↓ × OXT↓ × DA↓ × cortisol↑ = a biological barrier that financial incentives cannot overcome. Money corrects a CONSCIOUS decision but does not correct T levels, libido, or sperm quality. The Amish (TFR 6.5) receive no pronatalist support → BIOLOGY determines outcomes, not economics.

Epistemic level:E (empirical: every intervention is a documented failure)

Sources: OECD Family Database; Greksa 2002 Ann Hum Biol

08"Failure to Launch"

A growing share of young men (18–30) are not working, not in education, not in a relationship. USA: labor force participation fell 86%→81% 2000–2023. Japan: hikikomori (~1.5M). The share of sexless young men in the USA rose 28%→38% 2008–2018 (GSS).

Conventional explanation

Video games, pornography, economic insecurity. BUT: the hikikomori phenomenon began BEFORE social media (1990s). And: why specifically men?

BERM explanation

T↓ 25% in young people (Lokeshwar 2021) → motivation↓, competitiveness↓. DA↓ → the reward system requires stronger stimuli → video games/porn = EASIER dopamine source than social competition. OXT↓ → social desire↓. Cortisol↑ → aversion to new situations. Video games and porn are CONSEQUENCES (DA↓ → compensation), not causes.

Epistemic level:M|C

Sources: GSS 2018; Lokeshwar 2021 Eur Urol Focus 7:886–893

09The Insomnia Epidemic

Insomnia and declining sleep quality are a global trend. Short sleep (<6h) prevalence is rising especially among young people. The phenomenon also occurs in people who do NOT use screen devices in the evening.

Conventional explanation

Screen time, stress, caffeine. BUT: insomnia has also risen in groups where screen time is controlled.

BERM explanation

Two independent melatonin suppression pathways: Pathway 1 (blue light → melanopsin → SCN → melatonin↓) is well known. Pathway 2 (EMF → CRY/VGCC → SCN oscillation → melatonin↓) operates IN THE DARK (calves in darkness, Sci.Rep. 2015). Wi-Fi and electrical grid are active throughout the night.

AND: pineal gland calcification (PGC) is CUMULATIVE and IRREVERSIBLE → melatonin production capacity DECLINES with age faster than natural aging explains. "Orange glasses are not enough" because the EMF pathway bypasses them.

Epistemic level:M|C

Sources: Walker 2017 Why We Sleep; Sci.Rep. 2015 (calves in darkness)

10Precocious Puberty

Age at menarche declined from approximately 17 years (1800s) to 12–13 years (2000s). The decline CONTINUES even though nutritional status is already high.

Conventional explanation

Nutrition explains the 1800–1960 decline. EDCs (endocrine disrupting chemicals) explain part. BUT: why does the decline CONTINUE from 1960–2020 when nutrition is already adequate?

BERM explanation

Melatonin is a CAUSAL regulator of puberty: melatonin inhibits the GnRH pulse generator. Melatonin↓ → GnRH inhibition removed → puberty advances. CAUSAL evidence: pinealectomy/pineal tumor → melatonin=0 → precocious puberty (PMC10601200i, clinical). EMF → melatonin↓ (two pathways) + PGC accumulates → continued advancement.

Epistemic level:E (causal link clinically verified)

Sources: PMC10601200; Castellano et al. 2011 Mol Cell Endocrinol

11Political Polarization and Institutional Decay

Polarization has increased in all Western democracies since the 2000s. Trust in institutions is declining. The phenomenon crosses party lines and national borders.

Conventional explanation

Social media, income inequality. BUT: polarization began BEFORE social media (Heltzel & Laurin 2020: USA from 1994→). And: why simultaneously in all countries?

BERM explanation

OXT↓ → social trust↓. Cortisol↑ → threat motivation > cooperation motivation. Amygdala↑ / hippocampus↓ (VK55): threat-sensitive processing dominates. T↓ → defensiveness. BDNF↓ → black-and-white thinking↑. Social media is a CHANNEL, not a CAUSE. The biological susceptibility to polarization increases with the EMF cascade.

Epistemic level:M|C (analogous but mechanistically logical)

Sources: Heltzel & Laurin 2020 Curr Opin Behav Sci 34:112–117

12Decline of Religiosity and the "Meaning Crisis"

"Nones" (religiously unaffiliated) in the USA: 30% (2024) vs. 5% (1972). Therapy demand at record levels. "Meaning crisis" (Vervaeke). Religiosity correlates with TFR everywhere.

Conventional explanation

Secularization (education, science). BUT: the Amish are less educated AND religious AND fertile. EMF exposure differentiates better than education.

BERM explanation

Religious experience is neurobiological: 5-HT → transcendence, DA → ritual reward, OXT → belonging. EMF → all three↓ → the neurobiological capacity for spiritual experience weakens. The "meaning crisis" is a biological phenomenon, not a philosophical one.

Epistemic level:L* (analogous, novel, falsifiable)

Sources: Vervaeke 2019; GSS trend data

13The Loneliness Epidemic

The US Surgeon General declared loneliness an epidemic in 2023. 58% of US adults report loneliness (Cigna 2020). 15% of men report ZERO close friends (American Survey Center 2021) — a fivefold increase since 1990. Mortality risk: +26% (Holt-Lunstad 2015 meta, N=300,000+), equivalent to smoking 15 cigarettes per day. The trend began BEFORE social media and COVID only accelerated an already-ongoing process.

Conventional explanation

Urbanization, social media, lifestyle changes. BUT: (a) the phenomenon began before social media (1990→), (b) the conventional literature ITSELF identifies the biological mechanism but does NOT ask why it has changed at the population level.

The conventional literature's OWN biological model — Frontiers Psychiatry 2023: "Social connection may dampen HPA activation and impart anti-stress effects through the release of oxytocin. Oxytocin has a well-established role in suppressing HPA activity by inhibiting the release of corticotropin-releasing hormone from hypothalamic neurons." IJMS 2026: social isolation → conserved transcriptional response → proinflammatory genes↑ + antiviral gene expression↓.

BERM explanation

The conventional literature identifies the chain: OXT↓ → HPA↑ → cortisol↑ → inflammation → metabolic syndrome. The conventional literature does NOT ask: WHY has OXT declined at the POPULATION level? BERM answers: EMF → VGCC → Ca²⁺ → OXT secretion disruption (VK29) → population-level OXT↓ → loneliness↑ → cortisol↑ → disease.

This makes the loneliness epidemic BERM's strongest civilization-level argument because the mechanism is IDENTIFIED BY CONVENTIONAL SCIENCE ITSELF — only the upstream cause (EMF) is missing from their model.

AND: a positive feedback loop: OXT↓ → loneliness → LESS social contact → LESS OXT release → MORE loneliness → MORE cortisol↑ → MORE inflammation → etc. EMF initiates the cycle but the cycle SUSTAINS ITSELF.

Epistemic level:M|C (biological mechanism identified by conventional literature, BERM adds the upstream cause)

Sources: US Surgeon General 2023; Holt-Lunstad 2015 meta; Frontiers Psychiatry 2023; IJMS 2026 27:84; Cigna 2020; American Survey Center 2021

Summary Table

PhenomenonConventionalBERMLevelBERM advantage
1 Klimentidis paradoxNo comprehensiveCa²⁺→insulin+mel↓L*Cross-species
2 IQ decline"Environmental change"BDNF↓+mel↓M|CTiming + dissociation
3 Deaths of despairSocioeconomicT↓+DA↓+cort↑M|CBiological mechanism
4 Female happiness paradoxUnclearVGCC sensitivity+OXT↓M|CUniversality
5 Autoimmune epidemicHygiene hypothesisCa²⁺→NF-κB→ROSM|CAcceleration
6 Myopia pandemicNear work+outdoorsDA↓+LED→mel↓M|CLED risk factor
7 Pronatalist failureNo explanationQuadruple lockEAmish contrast
8 Failure to launchVideo games/pornT↓×OXT↓×DA↓M|CBiological substrate
9 Insomnia epidemicScreen timeEMF pathway ≠ lightM|CWorks in darkness
10 Precocious pubertyNutrition (1800–60)Mel↓→GnRH↑EPinealectomy evidence
11 Political polarizationSocial mediaOXT↓+amygdala↑M|CBegan before social media
12 Decline of religiositySecularization5-HT↓+OXT↓+DA↓L*Amish contrast
13 Loneliness epidemicSocial mediaOXT↓→HPA↑→cort↑M|CConv. identifies mechanism

CONVENTIONAL: 13 separate explanations for 13 separate phenomena.

BERM: 1 mechanism (EMF → Ca²⁺ → hormone cascade) → 13 manifestations = PARSIMONY: BERM is simpler AND more explanatorily powerful.

STRONGEST (E-level): pronatalist failure (#7), precocious puberty (#10).

STRONG (M|C): IQ (#2), Deaths of Despair (#3), autoimmune (#5), myopia (#6), loneliness (#13), female happiness (#4), insomnia (#9), failure to launch (#8), polarization (#11).

NOVEL, FALSIFIABLE (L*): Klimentidis (#1, requires replication), religiosity (#12).

References

  1. Klimentidis et al. 2011, Proc R Soc B 278:1626–1632
  2. LessWrong replication analysis 2023
  3. Brown et al. 2016, Obes Res Clin Pract 10:243–255
  4. Bratsberg & Rogeberg 2018, PNAS 115:6674–6678
  5. Dworak et al. 2023, Intelligence 101:101793
  6. Flynn & Shayer 2018
  7. Case & Deaton 2015, PNAS 112:15078–15083
  8. Case & Deaton 2020, Deaths of Despair (Princeton UP)
  9. PNAS 2024, doi:10.1073/pnas.2307656121
  10. Stevenson & Wolfers 2009, AEJ:EP 1:190–225
  11. Blanchflower & Bryson 2024, J Pop Econ 37:16
  12. Science Advances 2026, doi:10.1126/sciadv.adt1646
  13. GBD 2021, Lancet (autoimmune)
  14. NHC 2025, nationalhealthcouncil.org
  15. NCBI Bookshelf NBK605881 (2022)
  16. Holden et al. 2016, Ophthalmology 123:1036–1042
  17. Wang et al. 2021, JAMA Ophthalmol 139:293–300
  18. NEI 2025, Chiang report
  19. BMC Ophthalmol 2020, LED risk factor
  20. OECD Family Database
  21. Greksa 2002, Ann Hum Biol (Amish TFR)
  22. GSS 2018
  23. Lokeshwar et al. 2021, Eur Urol Focus 7:886–893
  24. Walker 2017, Why We Sleep
  25. Sci.Rep. 2015 (calves in darkness)
  26. PMC10601200 (pinealectomy → puberty)
  27. Castellano et al. 2011, Mol Cell Endocrinol
  28. Heltzel & Laurin 2020, Curr Opin Behav Sci 34:112–117
  29. Vervaeke 2019
  30. US Surgeon General 2023
  31. Holt-Lunstad 2015 meta, PLOS Med N=300K+
  32. Frontiers Psychiatry 2023, OXT→HPA→loneliness
  33. IJMS 2026 27:84, loneliness neuroendocrinology
  34. Cigna 2020, loneliness survey
  35. American Survey Center 2021, male friendships