# Optimocracy: The Evidence Machine Ten thousand jurisdictions have already tried your policy. They wrote down what happened. Your species skipped that step and went straight to arguing. ## The Only Two Numbers That Matter Two numbers. Just two. **Real after-tax median income growth.** Did the person in the middle get richer this year? Not GDP per capita, which looks great when three billionaires move into your city while everyone else’s rent doubles. **Median healthy life years.** How many years can the person in the middle expect to live in good health? Not average life expectancy, which counts the billionaire who replaced his blood six times as canceling out someone who died at 40. Why these two? Because everything important your governments do eventually makes people richer or less dead, and if it doesn’t do either, it wasn’t important. Your government currently measures success by how much money it spends, which is like a restaurant measuring success by how much food it buys. You could buy a mountain of ingredients and poison everyone. By your current metrics, that’s a good year. Your species engineered a pocket-sized device with 16 billion transistors, mass spectrometry, and supply chains spanning 43 countries. Then you built an algorithm that A/B tests billions of user interactions, optimizing hundreds of signals in real time, so that device can show you the optimal twerking video. That is more empirical rigor than your species applies to allocating its federal budget. The federal budget decides who gets medicine, who gets clean water, and who gets bombed. [55 million](../../knowledge/appendix/parameters-and-calculations.llms.md#sec-global_annual_deaths_curable_diseases) people die every year from diseases you already have treatments for. You optimized the twerking. You did not optimize the not-dying. Here’s what makes these numbers useful beyond measurement: your species already agrees on both goals. Nobody campaigns on “make people poorer and sicker.” But without a scoreboard, policy debates become tribal arguments about vibes. You forgot the question. You’re not arguing about whether people should be healthier and richer; you’re arguing about which policies achieve that, and nobody’s checking. Once you check, most of the argument disappears, because it turns out the answer isn’t left or right. It’s in the data from the 10,000 places that already tried it. Now that you know what we’re measuring, here’s how badly your species is doing at it. ## The Price of Not Checking The United States spends [300%](../../knowledge/appendix/parameters-and-calculations.llms.md#sec-us_vs_switzerland_spending_gap) percentage points more of GDP than Switzerland on government. Switzerland gets [6.5 years](../../knowledge/appendix/parameters-and-calculations.llms.md#sec-us_vs_switzerland_life_expectancy_gap) more years of life expectancy. One of these countries is doing it wrong. A rational civilization would check which one. Your species had a debate about it. The debate has been going on for 50 years. The Swiss are still winning. You’re paying more and dying sooner, and your response is to have opinions about it. [![Rich countries aren’t rich because of resources. They’re rich because their rules aren’t stupid. Poor countries have bad governments. It’s the institutions, not the dirt.](../../assets/images/optimocracy-paper/optimocracy-paper-section-the-scale-of-welfare-loss-empirical-foundations-bw-academic.jpg)](../../assets/images/optimocracy-paper/optimocracy-paper-section-the-scale-of-welfare-loss-empirical-foundations-bw-academic.jpg) Rich countries aren’t rich because of resources. They’re rich because their rules aren’t stupid. Poor countries have bad governments. It’s the institutions, not the dirt. Documented US governance waste totals [\$4.98 trillion (90% CI: \$4.39 trillion-\$5.61 trillion)](../../knowledge/appendix/parameters-and-calculations.llms.md#sec-us_gov_waste_total) ([17.3% (90% CI: 15.3%-19.5%)](../../knowledge/appendix/parameters-and-calculations.llms.md#sec-us_gov_waste_pct_gdp) of GDP). Globally, the opportunity cost of suboptimal policy reaches [\$101 trillion (90% CI: \$59.6 trillion-\$161 trillion)](../../knowledge/appendix/parameters-and-calculations.llms.md#sec-political_dysfunction_global_opportunity_cost_total) ([87.8% (90% CI: 51.8%-140%)](../../knowledge/appendix/parameters-and-calculations.llms.md#sec-political_dysfunction_global_opportunity_cost_pct_gdp) of GDP), putting your civilization’s governance efficiency at [51.8% (90% CI: 40.3%-64.6%)](../../knowledge/appendix/parameters-and-calculations.llms.md#sec-political_dysfunction_global_efficiency_score). Your species is running at roughly half its technological potential. Imagine building a car, then only turning on half the cylinders because the other half are controlled by a committee that meets once a year and disagrees about what “forward” means. (For the full accounting, see the [Political Dysfunction Tax](https://manual.warondisease.org/knowledge/appendix/political-dysfunction-tax.html)^([1](../references.llms.md#ref-political-dysfunction-tax-paper-2025)) and [US Efficiency Audit](https://manual.warondisease.org/knowledge/appendix/us-efficiency-audit.html)^([2](../references.llms.md#ref-us-efficiency-audit-paper-2025)).) Or consider the War on Drugs. Your species spends [\$90 billion (95% CI: \$60 billion-\$150 billion)](../../knowledge/appendix/parameters-and-calculations.llms.md#sec-us_gov_waste_drug_war) per year on it. When Nixon declared it in 1971, about 6,000 Americans died annually from drug overdoses^([3](../references.llms.md#ref-cdc-overdose-1980)). After 50 years and over a trillion dollars, that number exceeded 100,000^([4](../references.llms.md#ref-cdc-overdose-2023)). At no point did anyone check whether the policy was working. At no point did anyone stop funding it because it wasn’t. No sane species would spend a trillion dollars on something, watch the problem get 18 times worse, and increase the budget. Your species did exactly that. ## The Answer Key You Already Have Your planet has roughly 10,000 jurisdictions making different policy choices. Kansas cut education funding; Minnesota increased it. Fifty states adopted different minimum wages over 30 years. Portugal decriminalized drugs; Singapore didn’t. These are natural experiments, and the math can now figure out which policy caused which result, without needing anyone’s permission to run an experiment. The experiment already happened. You just weren’t paying attention. [![Optimocracy: measure what works, recommend what works, check if anyone listened, pay people who listened. It’s the revolutionary idea of doing the thing that works.](../../assets/images/optimocracy-paper/optimocracy-paper-section-the-mechanism-bw-academic.jpg)](../../assets/images/optimocracy-paper/optimocracy-paper-section-the-mechanism-bw-academic.jpg) Optimocracy: measure what works, recommend what works, check if anyone listened, pay people who listened. It’s the revolutionary idea of doing the thing that works. Same logic as your [decentralized FDA](../../knowledge/solution/dfda.llms.md)^([5](../references.llms.md#ref-dfda-spec-paper-2025),[6](../references.llms.md#ref-dfda-impact-paper-2025)): watch what actually happens, then analyze the data. Your [decentralized FDA](../../knowledge/solution/dfda.llms.md) applies this to medicine. The Evidence Machine applies it to governance. Instead of “which drug works?” you’re asking “which policy works?” Same question, higher body count. ## Why Knowing Isn’t Enough If you’re thinking “just publish the results and politicians will do the right thing,” I have some bad news about your species. The Copenhagen Consensus already publishes rigorous benefit-cost analyses^([7](../references.llms.md#ref-copenhagenconsensus2023)). Childhood vaccination: 101:1 returns. Pragmatic clinical trials: [439 (90% CI: 321-600)](../../knowledge/appendix/parameters-and-calculations.llms.md#sec-dfda_roi_rd_only):1. Agricultural subsidies: less than 1:1. The answer key is public. It’s been public for years. Your governments ignore it. You have the cheat sheet, and you’re still failing the test on purpose. [![Evidence says do this thing. Politicians say no because it won’t get them reelected. You built a system where saving lives loses votes.](../../assets/images/optimocracy-paper/optimocracy-paper-section-why-information-alone-fails-bw-academic.jpg)](../../assets/images/optimocracy-paper/optimocracy-paper-section-why-information-alone-fails-bw-academic.jpg) Evidence says do this thing. Politicians say no because it won’t get them reelected. You built a system where saving lives loses votes. Why? Because information doesn’t change incentives. A Princeton study analyzed 1,779 policy decisions and found that average citizens have “little or no independent influence” on policy outcomes^([8](../references.llms.md#ref-gilens2014)). Economic elites and organized interest groups drive policy. You already knew this (it’s covered in [Unrepresentative Democracy](../../knowledge/problem/unrepresentative-democracy.llms.md)). The point here is that publishing better data doesn’t fix the problem. Your politicians already know which programs produce value. They don’t act because acting doesn’t maximize getting votes, getting papers, or getting a nice job afterward selling access to their replacements. So there are two problems, and this chapter is only about the first one. The knowledge problem is “which policies actually work,” and it is solved by measurement nobody can corrupt. The incentive problem is “why would anyone act on the answer,” and it has [several solutions of varying price](https://manual.warondisease.org/knowledge/appendix/optimocracy-paper.html/#sec-adoption-mechanisms): an institution that adopts the recommendations because they are correct, a shareholder who points out that a company’s lobbying is losing its own shareholders money, a SuperPAC, or [bonds](../../knowledge/solution/incentive-alignment-bonds.llms.md)^([9](../references.llms.md#ref-iab-paper-2025)) paying a share of whatever gets redirected. Every one of them needs the same thing first, which is a number that is actually true. ## The Mechanism: Recommend, Track, Reward The Evidence Machine does three things. That’s it. Three things. Your species has difficulty with three things, so I’ll use small words. (It’s an appliance. You plug in policies, it tells you which ones work. Your species will find this concept exotic.) **Recommend.** The Optimitron has two settings. The [Optimal Budget Generator](https://obg.warondisease.org)^([10](../references.llms.md#ref-obg-paper-2025)) answers “how much should you spend on what?” The [Optimal Policy Generator](https://opg.warondisease.org)^([11](../references.llms.md#ref-opg-paper-2025)) answers “which laws should you enact, replace, or repeal?” Here’s a sample of what the budget output looks like, applied to the United States: | Category | Current | Optimal | Gap | Evidence | |---------------------------|---------|---------|--------------|----------------------| | Pragmatic clinical trials | \$0.5B | \$50B | **+\$49.5B** | A (RCTs) | | Vaccinations | \$8B | \$35B | +\$27B | A (RCTs) | | Military (discretionary) | \$850B | \$459B | -\$391B | C (benchmarks) | | Agricultural subsidies | \$25B | \$0B | -\$25B | A (welfare analysis) | You are spending 100 times less than optimal on figuring out which medicines work, and paying farmers \$25 billion a year to grow food nobody asked for. The Optimitron noticed. It also noticed you could cut \$391 billion from the murder budget and still have the largest military on the planet. The policy generator then does the same thing law by law: enact this, repeal that, adjust the other thing. Every recommendation traceable to what actually happened when another jurisdiction tried it. No opinions. Just receipts. **Track.** When politicians vote, record whether they aligned with the evidence-based recommendation. Senator Smith: 78% aligned. Senator Jones: 34% aligned. This information is public. Any citizen can check. There is a word for this. The word is “checking if the person you hired did the thing you hired them to do.” Your species finds this concept revolutionary, which tells you everything. Politicians who ignore the evidence must do so on the record. **Reward.** Something has to make the score matter. The cheapest version is a company whose lobbyists already have the senator’s phone number and are now selling the evidence-based budget instead ([the takeover](https://manual.warondisease.org/knowledge/appendix/loving-takeover.html)). The fastest version is a SuperPAC allocating campaign support proportional to alignment: follow evidence, get funded; ignore it, watch your opponent get funded. Same trick the NRA perfected, but pointed at “not dying” instead of “more guns.” The scoreboard does not care which one shows up. [![Instead of forcing politicians to be good, pay them to accidentally do good things while pursuing money. You can’t fix human nature, but you can redirect it.](../../assets/images/optimocracy-paper/optimocracy-paper-section-why-government-adoption-isn-t-required-bw-academic.jpg)](../../assets/images/optimocracy-paper/optimocracy-paper-section-why-government-adoption-isn-t-required-bw-academic.jpg) Instead of forcing politicians to be good, pay them to accidentally do good things while pursuing money. You can’t fix human nature, but you can redirect it. This doesn’t require government permission. The Evidence Machine operates as a permanent advisory layer outside government. The policy data is public, the votes are public, and publishing the comparison between them is just talking. Politicians still vote however they want. They can still ignore the evidence; it just costs them something now, which on Earth is apparently the only consequence that matters. The question isn’t “will politicians give up power?” (they won’t) but “will anyone act on an accurate scoreboard?” (several parties would, for several different reasons, which is the whole point of building it before deciding who). ## Corruption, But Make It Difficult “But won’t someone corrupt the measurement system?” Yes. This is the right question. It’s the only question that matters. Currently, your lobbying industry has thousands of capture points. Committee earmarks, agency decisions, regulatory rulings, budget amendments, riders on unrelated bills. Each one is cheap to influence. Your federal lobbyists spend [\$4.4 billion (95% CI: \$3.74 billion-\$5.06 billion)](../../knowledge/appendix/parameters-and-calculations.llms.md#sec-us_total_lobbying_annual) per year^([12](../references.llms.md#ref-opensecrets-lobbying-2024)) with estimated 100:1 returns^([13](../references.llms.md#ref-drutman2015)). Your democracy is a vending machine, and the buttons are labeled. [![Lobbyists currently have thousands of people to corrupt. Optimocracy gives them one target protected by multiple watchdogs. You’re trying to make corruption impractical instead of illegal.](../../assets/images/optimocracy-paper/optimocracy-paper-section-capture-resistance-bw-academic.jpg)](../../assets/images/optimocracy-paper/optimocracy-paper-section-capture-resistance-bw-academic.jpg) Lobbyists currently have thousands of people to corrupt. Optimocracy gives them one target protected by multiple watchdogs. You’re trying to make corruption impractical instead of illegal. The Evidence Machine collapses all those capture points to a single target: the measurement methodology. Here’s the heist: simultaneously bribe the Census Bureau, the Federal Reserve, the Bureau of Labor Statistics, academic institutions, AND decentralized citizen surveys. All without detection. All at the same time. All institutions with different governance structures, different funding sources, different methodologies, and different reasons to hate each other. This is not a corruption strategy. This is the plot of a movie where the criminals lose. Here’s how it works in practice. Five independent sources measure median income growth: | Source | Reported Growth | |:--------------------------------------------------------|:----------------| | Census Bureau (American Community Survey) | +2.1% | | Federal Reserve (Survey of Consumer Finances) | +2.3% | | Bureau of Labor Statistics (Current Population Survey) | +1.9% | | University of Michigan (Panel Study of Income Dynamics) | +2.2% | | Tax Foundation (IRS data analysis) | +2.0% | Take the median: **+2.1%**. If one source reports +5.0% (because someone bribed them), the median throws it out automatically. No investigation needed. No whistleblower needed. No committee hearing. Math does the work. These five sources overlap in some inputs. The sixth source, decentralized citizen surveys, breaks that dependence by adding a methodology-independent stream collected directly from millions of humans. One person lying has approximately zero effect on the median. This is statistics, not voting. Your species has spent centuries making corruption illegal. It hasn’t worked, because laws are enforced by the same humans who are being bribed. The alternative is obvious: make corruption impractical. There’s a difference between “you shouldn’t steal” and “the vault has five locks held by five people who hate each other.” Your species tried door number one for 3,000 years. We recommend door number two. This is also why it’s different from every previous attempt at technocratic governance. Soviet central planning had one source of truth (the Politburo). Credit rating agencies had one source of truth (the agency paid by the people being rated, which is like letting students grade their own exams and then being surprised when everyone gets an A). Both were captured immediately, because corrupting one institution is a Tuesday. Corrupting five independent institutions simultaneously, without any of them noticing or telling anyone, is a conspiracy theory. The expensive kind that doesn’t work. Why not 50 metrics? Because each additional target creates a new way to cheat, and your species needs no encouragement in that department. Markets figured this out: firms optimize profit, not 200 sub-metrics. Two broad, hard-to-fake numbers are easier to audit than 50 narrow ones. And these particular numbers are very hard to fake. You can’t fabricate purchasing power at scale without actually improving household economics. Mortality is binary (the most binary thing there is). You can’t fake everyone being “less dead.” [![Some numbers are easy to fake. GDP per capita looks great if three billionaires move in. Median income and healthy life years are harder to game. You can’t fake everyone being less dead.](../../assets/images/optimocracy-paper/optimocracy-paper-section-why-goodhart-s-law-doesn-t-apply-here-bw-academic.jpg)](../../assets/images/optimocracy-paper/optimocracy-paper-section-why-goodhart-s-law-doesn-t-apply-here-bw-academic.jpg) Some numbers are easy to fake. GDP per capita looks great if three billionaires move in. Median income and healthy life years are harder to game. You can’t fake everyone being less dead. “But correlation isn’t causation!” Yes. Thank you. Your species discovered this in the 1800s and has been using it as an excuse to ignore data ever since. The Optimitron doesn’t just check whether policies and outcomes happened in the same room. It uses the fact that 10,000 jurisdictions adopted different policies at different times to isolate what actually caused what. (The boring details: the [technical specification](https://manual.warondisease.org/knowledge/appendix/optimal-policy-generator-spec.html) scores every causal claim against nine criteria, and if the timing is wrong, the score is automatically zero, no matter how pretty the correlation looks.) ## Putting It Together The full loop: the Evidence Machine identifies what works, [somebody with a financial reason to care](https://manual.warondisease.org/knowledge/appendix/optimocracy-paper.html/#sec-adoption-mechanisms) makes the politicians act on it, the [1% Treaty](https://manual.warondisease.org/knowledge/solution/1-percent-treaty.html)^([14](../references.llms.md#ref-1-percent-treaty-paper-2025)) ^([15](../references.llms.md#ref-1-pct-treaty-impact-paper-2025)) funds it, and [Wishocracy](../../knowledge/solution/wishocracy.llms.md)^([16](../references.llms.md#ref-wishocracy-paper-2025)) allocates the research funds. The Evidence Machine tells governments which policies work. [Wishocracy](../../knowledge/solution/wishocracy.llms.md) tells the research fund where to aim. Your species calls this “a bold new paradigm.” Everyone else calls it “an obvious system.” It required four chapters and a bibliography because you’re you. [![Tribal politics: my team good, your team bad. Optimocracy: did anyone get healthier or richer. One is sports, the other is governance.](../../assets/images/optimocracy-paper/optimocracy-paper-section-depolarization-bw-academic.jpg)](../../assets/images/optimocracy-paper/optimocracy-paper-section-depolarization-bw-academic.jpg) Tribal politics: my team good, your team bad. Optimocracy: did anyone get healthier or richer. One is sports, the other is governance. And here’s why the whole thing ratchets. Every expansion pays whoever pushed for it, whether that is a shareholder holding a repriced company or a bondholder collecting a share of the redirected money, and their winnings fund more evidence collection, which strengthens the case for the next expansion. Evidence begets funding begets evidence. It’s the same self-reinforcing loop as the [Military Industrial Complex](../../knowledge/solution/aligning-incentives.llms.md), except instead of manufacturing orphans, it manufactures data about how to stop manufacturing orphans. Now that you know how the Optimitron works (congratulations, on Wishonia this is taught to children), the next chapter shows you how [8 billion people allocate the research funds](../../knowledge/solution/wishocracy.llms.md). ## The Referee: Who Measures Whether It Worked Everything above describes how the Evidence Machine works. This section describes who runs it, because “an algorithm that nobody can corrupt” still requires someone to plug it in. The Measurement Authority (the Referee) is whoever locks the ruler before the game starts, reads the scoreboard at regular intervals, announces whether you’ve hit the thresholds for releasing prize money, and settles arguments when someone says the numbers are wrong. On Wishonia this job is given to the most boring person available. Boring is a feature. **What the Referee does:** 1. Locks the baseline methodology at game start (prevents retroactive methodology changes from triggering false release). 2. Reads WHO Health-Adjusted Life Expectancy and World Bank median income data annually. 3. Cross-checks institutional data against the five independent sources described above (Census Bureau, Federal Reserve, BLS, academic institutions, decentralized citizen surveys). 4. Publishes cryptographically signed determinations of whether graduated release thresholds have been met (10% at +0.5 HALY, 25% at +1.0 HALY, 50% at +2.0 HALY, 100% at +5.0 HALY, with equivalent income thresholds). 5. Accepts bonded challenges (anyone who catches gaming can post a bond, present evidence, and trigger independent review). 6. Routes disputes to an academic panel for adjudication. **What the Referee does not do:** - Hold the money. That is the [Vault’s](../../knowledge/solution/dih.llms.md) job. - Lobby for the treaty. That is the [Sword’s](../../knowledge/legal/legal-framework.llms.md) job. - Verify voter identity. That is the [Bouncer’s](https://manual.warondisease.org/knowledge/appendix/earth-optimization-prize-protocol.html) job. **Why it cannot be the Vault:** The entity that decides whether to release the money cannot be the entity holding the money. Your species learned this lesson approximately 4,000 years ago and has been re-learning it every century since. **Why it cannot be the Sword:** The entity lobbying for the outcome cannot measure whether the outcome occurred. Your current system lets governments measure their own performance and announce that they are doing an excellent job. Your species calls this “self-assessment.” I call it “letting the student grade the exam.” **What kind of organization fits:** The ideal Referee is boring, methodologically rigid, and has no financial interest in either branch of the prize payout. University health economics departments, WHO-affiliated statistical groups, or a consortium of institutions that already measure these numbers (and have reputations staked on measuring them correctly) are the natural candidates. You want the person who is genuinely excited about error margins. Your species produces these people. You just usually underpay them. **Redundancy:** Five independent data sources (Census Bureau, Federal Reserve, BLS, University of Michigan, Tax Foundation) plus decentralized citizen surveys all feed the same numbers. Any two honest analysts reading the same sources get the same answer. The Referee just signs the determination. Everyone else can check the homework from the same public data. If the Referee’s number disagrees with what the raw sources say, anyone can post a bond, present evidence, and trigger independent review. Someone must sign the determination (otherwise nobody is responsible). Everyone can catch a lie (otherwise nobody is safe). **Succession:** The methodology is published and locked. If the Referee disappears, a replacement panel can pick up the locked methodology and continue measuring. The data sources (WHO, World Bank, national statistical agencies) exist independently of whoever reads them. For the full technical specification, formal models, and threat analysis, see the [Optimocracy academic paper](https://manual.warondisease.org/knowledge/appendix/optimocracy-paper.html)^([17](../references.llms.md#ref-optimocracy-paper-2025)). For the gory details on how the recommendation engine decides you’re spending too much on corn and too little on not dying: [Optimal Budget Generator](https://obg.warondisease.org)^([10](../references.llms.md#ref-obg-paper-2025)) and [Optimal Policy Generator](https://opg.warondisease.org)^([11](../references.llms.md#ref-opg-paper-2025)). 1\. Sinn, M. P. *The Political Dysfunction Tax*. (2025) doi:[10.5281/zenodo.18603840](https://doi.org/10.5281/zenodo.18603840) *Quantifying the gap between current global governance and theoretical maximum welfare, estimating a 31-53% efficiency score and \$101 trillion in annual opportunity costs.* 2\. Sinn, M. P. *United States Efficiency Audit*. (2025) doi:[10.5281/zenodo.18447476](https://doi.org/10.5281/zenodo.18447476) *Systems audit estimating an annual U.S. efficiency gap of \$4.9T, with \$2.45T recoverable at OECD-median performance across direct spending waste, compliance burden, policy-induced GDP loss, and system inefficiency.* 3\. National Center for Health Statistics. [Drug poisoning deaths in the united states, 1980–2008](https://www.cdc.gov/nchs/products/databriefs/db81.htm). (2011) *The number of drug poisoning deaths increased sixfold from about 6,100 in 1980 to 36,500 in 2008.* 4\. National Center for Health Statistics. [Drug overdose deaths in the united states, 2003–2023](https://www.cdc.gov/nchs/products/databriefs/db522.htm). (2025) *Drug overdose deaths in the United States exceeded 100,000 annually beginning in 2021, with a peak of approximately 111,000 in 2023.* 5\. Sinn, M. P. *The Continuous Evidence Generation Protocol: Two-Stage Validation (RWE → Pragmatic Trials)*. (2025) doi:[10.5281/zenodo.18203375](https://doi.org/10.5281/zenodo.18203375) *We present the Predictor Impact Score (PIS), a novel composite metric operationalizing Bradford Hill causality criteria for automated signal detection from aggregated N-of-1 observational studies. Combined with pragmatic trial confirmation (based on evidence from 108+ embedded trials), this two-stage framework would generate validated outcome labels at 44.1x lower cost than traditional Phase III trials. This enables continuous, population-scale pharmacovigilance and precision dosing recommendations.* 6\. Sinn, M. P. *Ubiquitous Pragmatic Trial Impact Analysis*. (2025) doi:[10.5281/zenodo.18243914](https://doi.org/10.5281/zenodo.18243914) *Only 15 diseases/year get their first treatment each year. With 6,650 diseases lacking effective treatments, the backlog would take 443 years to clear. Integrating pragmatic trials into standard healthcare increases trial capacity 12.3x, cutting that timeline from 443 years to 36 years. The average untreated disease gets a treatment 212 years earlier, saving 10.7 billion deaths at \$9.62 per year of healthy life saved.* 7\. Copenhagen Consensus. [Halftime for SDGs: Child immunization](https://copenhagenconsensus.com/publication/halftime-sdgs-child-immunization). (2023). 8\. Gilens, M. & Page, B. I. [Testing theories of american politics: Elites, interest groups, and average citizens](https://doi.org/10.1017/S1537592714001595). *Perspectives on Politics* **12**, 564–581 (2014). 9\. Sinn, M. P. *Incentive Alignment Bonds: Making Public Goods Financially and Politically Profitable*. (2025) doi:[10.5281/zenodo.18203221](https://doi.org/10.5281/zenodo.18203221) *Government spending is optimized for lobbying intensity, not net societal value. Programs with 100:1 benefit-cost ratios get billions while programs with negative returns get hundreds of billions. Incentive Alignment Bonds flip this by creating a capital pool that rewards politicians (via campaign support and post-office opportunities) for funding high-NSV programs over low-NSV alternatives. The result: public good becomes private profit for both investors and elected officials.* 10\. Sinn, M. P. *The Optimal Budget Generator: A Causal Inference Protocol for Maximizing Median Health and Wealth Through Public Goods Funding*. (2025) doi:[10.5281/zenodo.18356209](https://doi.org/10.5281/zenodo.18356209) *The Optimal Budget Generator (OBG) uses causal inference, diminishing returns modeling, and cost-effectiveness evidence to determine optimal public goods funding levels that maximize two welfare metrics: real after-tax median income growth and median healthy life years. For each spending category, OBG estimates an Optimal Spending Level (OSL) and produces a gap analysis showing where current government budgets are over- or underfunded relative to evidence-based benchmarks. The Budget Impact Score (BIS) measures confidence in each recommendation based on the quality of causal evidence.* 11\. Sinn, M. P. *The Optimal Policy Generator: A Causal Inference Protocol for Maximizing Median Health and Wealth Through Public Policy*. (2025) doi:[10.5281/zenodo.18603834](https://doi.org/10.5281/zenodo.18603834) *The Optimal Policy Generator (OPG) produces systematic public policy recommendations for jurisdictions at any level (country, state, city), generating prioritized enact/replace/repeal/maintain recommendations to maximize real after-tax median income growth and median healthy life years, based on quasi-experimental evidence from centuries of policy variation data.* 12\. OpenSecrets. [Federal lobbying hit record \$4.4 billion in 2024](https://www.opensecrets.org/news/2025/02/federal-lobbying-set-new-record-in-2024/). (2024) *Total federal lobbying reached record \$4.4 billion in 2024. The \$150 million increase in lobbying continues an upward trend that began in 2016. Additional sources: https://www.opensecrets.org/news/2025/02/federal-lobbying-set-new-record-in-2024/* . 13\. Drutman, L. *The Business of America Is Lobbying*. (Oxford University Press, 2015). doi:[10.1093/acprof:oso/9780190215514.001.0001](https://doi.org/10.1093/acprof:oso/9780190215514.001.0001). 14\. Sinn, M. P. *The 1% Treaty*. (2025) doi:[10.5281/zenodo.20076511](https://doi.org/10.5281/zenodo.20076511) *Your governments possess nuclear weapons sufficient to end civilization 122 times but have not cured Alzheimer’s once. This treaty asks them to be 1% more rational.* 15\. Sinn, M. P. *The 1% Treaty: An Incentive-Compatible Approach to Ending War and Disease*. (2025) doi:[10.5281/zenodo.18161560](https://doi.org/10.5281/zenodo.18161560) *6,650 diseases have zero FDA-approved treatments; at current trial capacity, exploring them takes  443 years. Redirecting 1% of military spending scales capacity 12.3x, cutting the timeline to  36 years and preventing 10.7 billion deaths. At \$0.02/DALY, 9.3kx more cost-effective than the best existing interventions. The result holds across every specified adoption pathway.* 16\. Sinn, M. P. *Wishocracy: Solving the Democratic Principal-Agent Problem Through Pairwise Preference Aggregation*. (2025) doi:[10.5281/zenodo.18205881](https://doi.org/10.5281/zenodo.18205881) *Representative democracy suffers from an inescapable principal-agent problem where elected officials’ incentives diverge from citizen welfare. Wishocracy introduces RAPPA (Randomized Aggregated Pairwise Preference Allocation), which aggregates citizen preferences through cognitively tractable pairwise comparisons and creates accountability via Citizen Alignment Scores that channel electoral resources toward politicians who actually represent what citizens want.* 17\. Sinn, M. P. *Optimocracy: Causal Inference on Cross-Jurisdictional Policy Data to Maximize Median Health and Wealth*. (2025) doi:[10.5281/zenodo.18356213](https://doi.org/10.5281/zenodo.18356213) *Thousands of jurisdictions have made different policy and budget choices over decades, creating a natural experiment. Optimocracy applies causal inference to this cross-jurisdictional time-series data to identify which policies predict above-average median income and healthy life years. It then publishes evidence-based recommendations for every major vote, tracks politician alignment, and funds aligned candidates via SuperPAC, making suboptimal policy politically expensive while preserving democratic structures.* 18\. Drug Policy Alliance. [The drug war by the numbers](https://drugpolicy.org/drug-war-stats/). (2021) *Since 1971, the war on drugs has cost the United States an estimated \$1 trillion in enforcement. The federal drug control budget was \$41 billion in 2022. Mass incarceration costs the U.S. at least \$182 billion every year, with over \$450 billion spent to incarcerate individuals on drug charges in federal prisons.* 19\. World Health Organization. WHO global health estimates 2024. *World Health Organization* (2024) *Comprehensive mortality and morbidity data by cause, age, sex, country, and year Global mortality:  55-60 million deaths annually Lives saved by modern medicine (vaccines, cardiovascular drugs, oncology):  12M annually (conservative aggregate) Leading causes of death: Cardiovascular disease (17.9M), Cancer (10.3M), Respiratory disease (4.0M) Note: Baseline data for regulatory mortality analysis. Conservative estimate of pharmaceutical impact based on WHO immunization data (4.5M/year from vaccines) + cardiovascular interventions (3.3M/year) + oncology (1.5M/year) + other therapies. Additional sources: https://www.who.int/data/gho/data/themes/mortality-and-global-health-estimates* .