Saturday, February 21, 2026

Economics of animals? ft. Adam Smith

Adam Smith (Wealth of Nations, book 1, chapter 2) wrote:

This division of labour, from which so many advantages are derived, is not originally the effect of any human wisdom, which foresees and intends that general opulence to which it gives occasion. It is the necessary, though very slow and gradual consequence of a certain propensity in human nature which has in view no such extensive utility; the propensity to truck, barter, and exchange one thing for another.

Whether this propensity be one of those original principles in human nature of which no further account can be given; or whether, as seems more probable, it be the necessary consequences of the faculties of reason and speech, it belongs not to our present subject to inquire. It is common to all men, and to be found in no other race of animals, which seem to know neither this nor any other species of contracts. Two greyhounds, in running down the same hare, have sometimes the appearance of acting in some sort of concert. Each turns her towards his companion, or endeavours to intercept her when his companion turns her towards himself. This, however, is not the effect of any contract, but of the accidental concurrence of their passions in the same object at that particular time. Nobody ever saw a dog make a fair and deliberate exchange of one bone for another with another dog. Nobody ever saw one animal by its gestures and natural cries signify to another, this is mine, that yours; I am willing to give this for that. When an animal wants to obtain something either of a man or of another animal, it has no other means of persuasion but to gain the favour of those whose service it requires. A puppy fawns upon its dam, and a spaniel endeavours by a thousand attractions to engage the attention of its master who is at dinner, when it wants to be fed by him. Man sometimes uses the same arts with his brethren, and when he has no other means of engaging them to act according to his inclinations, endeavours by every servile and fawning attention to obtain their good will. He has not time, however, to do this upon every occasion. In civilized society he stands at all times in need of the co-operation and assistance of great multitudes, while his whole life is scarce sufficient to gain the friendship of a few persons. In almost every other race of animals each individual, when it is grown up to maturity, is entirely independent, and in its natural state has occasion for the assistance of no other living creature. But man has almost constant occasion for the help of his brethren, and it is in vain for him to expect it from their benevolence only. He will be more likely to prevail if he can interest their self-love in his favour, and show them that it is for their own advantage to do for him what he requires of them. Whoever offers to another a bargain of any kind, proposes to do this. Give me that which I want, and you shall have this which you want, is the meaning of every such offer; and it is in this manner that we obtain from one another the far greater part of those good offices which we stand in need of. It is not from the benevolence of the butcher, the brewer, or the baker that we expect our dinner, but from their regard to their own interest. We address ourselves, not to their humanity but to their self-love, and never talk to them of our own necessities but of their advantages. Nobody but a beggar chooses to depend chiefly upon the benevolence of his fellow-citizens. Even a beggar does not depend upon it entirely. The charity of well-disposed people, indeed, supplies him with the whole fund of his subsistence. But though this principle ultimately provides him with all the necessaries of life which he has occasion for, it neither does nor can provide him with them as he has occasion for them. The greater part of his occasional wants are supplied in the same manner as those of other people, by treaty, by barter, and by purchase. With the money which one man gives him he purchases food. The old clothes which another bestows upon him he exchanges for other old clothes which suit him better, or for lodging, or for food, or for money, with which he can buy either food, clothes, or lodging, as he has occasion.

These are broad sweeping statements about humans and animals which today would be criticized, but nevertheless, it does seem true that humans are the only objects of study by economics, decision theory, and studies of agency more broadly. Expound upon this topic.

Smith is doing two things at once in that passage:

  1. giving an origin story for division of labour (“it’s a slow consequence of our propensity to exchange”), and
  2. drawing a sharp species boundary (“contracts” and deliberate exchange are uniquely human).

A lot of the 18th-century biology in the contrast is dated, but the underlying question is still live: how far do “economic” and “agentic” explanations reach beyond humans, and where do they stop being the same kind of thing?

Economics as a subject vs economics as a toolkit

If “economics” means markets with prices, money, firms, contracts, property rights, and institutions, then yes—its natural home is humans (and human-like institutions).

But if “economics” means allocating scarce resources under constraints, then it’s hard to avoid animals. Modern behavioral ecology is basically “economics of survival and reproduction”: animals face tradeoffs (energy vs. risk, present vs. future, exploration vs. exploitation) and you can model them with optimization and choice under constraints.

A canonical example is optimal foraging theory and Charnov’s Marginal Value Theorem, which predicts when a forager should leave a food “patch” based on diminishing returns and travel time. (ScienceDirect) A standard synthesis frames foraging explicitly as “economic analyses of animal feeding behavior.” (De Gruyter Brill)

So: economics-the-discipline often studies humans, but economics-the-mathematics is used all over biology.

“Markets” without money: biological market theory

Smith’s “no contracts among animals” claim looks less solid once you broaden “exchange” beyond explicit bargaining. A big line of work treats many animal interactions as markets where partner choice and competition to be chosen create something like supply-and-demand “prices,” even when the “currency” is grooming, tolerance, access, or effort.

That’s basically what Biological Market Theory proposes. (EurekaMag) And it’s not just metaphor—there are empirical tests showing “market effects” (prices changing with supply).

Examples:

  • Female baboons: grooming time functions like a “payment,” and the “price” of infant handling varies with the number of infants available (a supply effect). (ScienceDirect)
  • Grooming reciprocity in baboons: framed explicitly as market forces shaping exchange patterns. (PMC)
  • Bonobos: recent work analyzes sex and grooming as exchangeable commodities in a daily “market.” (Nature)

These systems don’t require language or legal contracts; they require (a) repeated interaction, (b) some ability to choose partners, and (c) enough cognition (or evolved heuristics) to respond to who offers what.

Cleaner fish: partner choice, “punishment,” and reputations

One of the cleanest (no pun intended) demonstrations of market-like dynamics is the cleaner wrasse–client fish mutualism.

  • Experiments show cleaners prioritize “choosy clients” (those who can leave and go elsewhere) over “resident clients” (those stuck with one station), matching the idea that outside options change bargaining power. (Libra)
  • Clients can curb cheating via partner switching or punishment, which stabilizes cooperation. (PubMed)
  • There’s even evidence of something akin to reputation/image scoring affecting cooperation. (Nature)

What’s striking here is that you can analyze this with the same strategic logic economists use (outside options, incentives, enforcement), even though there’s no written contract.

And the bridge back to “decision theory” is explicit: researchers model what kinds of learning machinery are required to solve the cleaner-fish “market task” using reinforcement-learning theory. (PubMed)

Primates: barter-like behavior exists, but it’s limited

Smith says nobody ever saw an animal “make a fair and deliberate exchange.” Today we have seen exchange-like behavior—often in controlled settings—but it also highlights what may be missing relative to humans.

  • Capuchins have been trained to trade tokens for food and show strong reactions to unequal outcomes (“unequal pay”), which researchers interpret (with debate) as a precursor to fairness/inequity sensitivity. (Nature)
  • Chimpanzees will barter in some contexts (including giving up lower-value food to get higher-value food), but they don’t trade whenever it would benefit them; one proposed explanation is weak “ownership” norms and/or high perceived risk of defection. (PubMed)

So animals can “exchange,” but the scope and reliability often look different from human trade—especially when you need stable property, delayed reciprocity, or guarantees.

Why humans still look special (and why Smith’s core intuition survives)

Even if Smith overstated the uniqueness of exchange, a refined version of his point still has bite:

  • Generalized, scalable exchange: Humans trade with strangers routinely, and not just via repeated dyadic relationships. This depends on norms, reputations, institutions, and often third-party enforcement.
  • Abstract representations: money, accounting, standardized measures, transferable property claims.
  • Commitment devices: contracts, courts, organizational forms, “credible commitments” that make specialization safe at scale.
  • Cumulative cultural evolution: we inherit practices (weights, writing, double-entry bookkeeping, legal templates) that massively extend what any individual could negotiate ad hoc.

Animals can have reciprocity, partner choice, and even rudimentary “market effects,” but human economies are weirdly institution-heavy—and that’s what turns small-scale exchange into complex division of labor spanning millions of people.

Where this leaves “agency”

Modern work tends to treat agency as graded rather than all-or-nothing:

  • Many organisms behave as if they’re optimizing (e.g., foraging models), whether by cognition, learning, or evolved heuristics. (ScienceDirect)
  • Some species show strategic social behavior consistent with incentives, partner choice, punishment, and reputation-like dynamics. (Libra)
  • Humans add a layer of explicit reasons, shared symbols, and institutional commitments that makes “economic agency” in the full modern sense far more portable and scalable.

So the cleanest way to reconcile Smith with current evidence is:

  • Economics as “choice under scarcity” applies broadly across animals.
  • Economics as “institutionalized exchange and production” is overwhelmingly human.
  • The boundary isn’t “animals don’t exchange”; it’s that humans evolved (and culturally accumulated) the machinery that makes exchange general, explicit, and enforceable, which is what supercharges division of labor.

If you want, I can map this into a tighter taxonomy—e.g., reciprocity → partner choice → market effects → property norms → enforceable contracts—and show where different species plausibly sit on that ladder.

Thursday, February 19, 2026

Modal Natural Law

the parallel between deontic and alethic modalities is very convenient for natural law theory

sketch out a formal natural law theory that leans on this by having the same modalities be alethic or deontic depending on whether it’s a free being

Here’s a compact “one-operator” natural law theory that exploits the structural parallel between alethic and deontic modality by letting the same modal vocabulary become alethic or deontic depending on whether the subject is a free being.


1) Language

Two sorts of things:

  • Entities: \(x,y,\dots\)
  • Worlds: \(w,v,\dots\)

Predicates / relations:

  • \(\mathrm{Free}(x)\): \(x\) is a free (rational/volitional) agent.
  • \(\mathrm{Nat}(x)\): the “nature” (essence/functional organization) of \(x\). (Treat as a parameter supplying constraints.)
  • \(\mathrm{End}(x,e)\): \(e\) is a proper end \(telos\) of \(x\).
  • \(\mathrm{Means}(e,\varphi)\): \(\varphi\) is a constitutive means for \(e\).
  • \(\mathrm{Act}_x(\varphi)\): “\(x\) sees to it that \(\varphi\)” (optional, but helpful for deontic readings).
  • \(\mathrm{Flour}(x)\): \(x\) flourishes / realizes its form well.

One modal pair, indexed by subject:

  • \(\Box_x \varphi\)
  • \(\Diamond_x \varphi := \neg \Box_x \neg \varphi\)

Intended neutral gloss of \(\Box_x\):

“\(\varphi\) holds by the law of \(x\)’s nature.”

The trick is that “law of nature” bites as necessity for non-free beings, and as obligation for free beings.


2) Semantics: one frame family, different constraints

Model:
\[
\mathcal{M}=(W,{R_x}_{x\in E},V,\mathrm{Free},\mathrm{Nat},\dots)
\]

Truth clause:
\[
\mathcal{M},w \vDash \Box_x \varphi \quad\text{iff}\quad \forall v,(wR_x v \rightarrow \mathcal{M},v \vDash \varphi).
\]

Now impose different frame conditions on \(R_x\) depending on freedom:

(A) Non-free beings: alethic (necessity)

If \(\neg \mathrm{Free}(x)\), then \(R_x\) is reflexive (at least), optionally S4/S5-ish if you like strong natural necessity:

  • Reflexive: \(\forall w, (wR_x w)\)
    validates T: \(\Box_x \varphi \to \varphi\)

Intuition: non-free things “follow” their natures as necessities (acorns become oaks unless impeded; electrons repel, etc.). When the modal says “must,” it’s literally must.

(B) Free beings: deontic (obligation)

If \(\mathrm{Free}(x)\), require \(R_x\) to be serial (at least):

  • Serial: \(\forall w,\exists v, (wR_x v)\)
    validates D: \(\Box_x \varphi \to \Diamond_x \varphi\)

But do not require reflexivity, so you do not validate T.
That blocks “ought implies is”:

  • For free \(x\): \(\Box_x \varphi\) does not entail \(\varphi\) at the actual world.

Intuition: if you can fail, then “bound by nature” shows up as practical necessity (obligation), not as guaranteed fact.

So the same operator \(\Box_x\) yields:

  • non-free \(x\): natural necessity
  • free \(x\): natural obligation

3) Core “Natural Law” principles

Now add axioms that make this natural-law-shaped rather than just “modal toggling.”

NL1. Teleological grounding

A minimal teleology-to-law schema:

\[
\mathrm{End}(x,e)\ \wedge\ \mathrm{Means}(e,\varphi)\ \to\ \Box_x \varphi.
\]

Reading: if \(\varphi\) is constitutive of realizing a proper end of \(x\), then \(\varphi\) is required by \(x\)’s nature.

  • For non-free \(x\), this is an alethic requirement: the unfolding of form.
  • For free \(x\), this becomes a deontic requirement: what practical reason must treat as action-guiding.

NL2. Freedom-sensitive compliance

Make the “is/ought split” explicit:

\[
\neg \mathrm{Free}(x) \to (\Box_x \varphi \to \varphi) \qquad\text{(necessity entails fact)}
\]
\[
\mathrm{Free}(x) \to \neg(\Box_x \varphi \to \varphi) \qquad\text{(obligation needn’t be met)}
\]

(Second line is not a single axiom in normal systems, but you can enforce it by not giving free agents reflexivity.)

NL3. Ought implies can (internalized)

Use the serial/D condition for free agents as the modal version:

\[
\mathrm{Free}(x) \to (\Box_x \varphi \to \Diamond_x \varphi).
\]

This is “ought implies can” in the same modality.

NL4. Practical form: obligations target agency

If you want obligations to be about what the agent does, tie \(\Box_x\) to agency:

\[
\mathrm{Free}(x)\ \wedge\ \Box_x \varphi \to \Box_x,\mathrm{Act}_x(\varphi)
\]

(or instead define obligation as \(\Box_x \mathrm{Act}_x(\varphi)\) and keep \(\varphi\) as outcome propositions.)


4) The natural law “bridge” without an is/ought fallacy

In this setup, the classical natural law move:

“From facts about nature to norms”

is recast as:

“From teleological structure to \(\Box_x\)-claims; whether those are is-like or ought-like depends on \(\mathrm{Free}(x)\).”

So you never infer an “ought” from a bare “is.” You infer a modal claim (“required by nature”), and then the logic itself tells you what kind of requirement it is, because the subject is free or not.

A handy definitional gloss:

  • Natural necessity: \(\mathrm{NatNec}(x,\varphi) := \neg\mathrm{Free}(x)\wedge \Box_x\varphi\)
  • Natural obligation: \(\mathrm{NatOught}(x,\varphi) := \mathrm{Free}(x)\wedge \Box_x\varphi\)

Same \(\Box\), different mode of governance.


5) Defect and wrongdoing as one notion, two manifestations

Define defect relative to nature:

\[
\mathrm{Defect}(x,\varphi) := \Box_x \varphi \wedge \neg \varphi.
\]

  • If \(\neg \mathrm{Free}(x)), (\mathrm{Defect}(x,\varphi)\) is typically impossible unless you also model impediments (injury, interference). Defect is “broken functioning.”
  • If \(\mathrm{Free}(x)), (\mathrm{Defect}(x,\varphi)\) is exactly the shape of wrongdoing: an obligation unmet.

This yields a unified natural law idea:

vice is a kind of malfunction in a rational animal.


6) Tiny illustrative example

Let \(a\) be an acorn, \(h\) a human.

  • \(\neg \mathrm{Free}(a)\), \(\mathrm{Free}(h)\)
  • \(\mathrm{End}(a,\text{oak})\), \(\mathrm{Means}(\text{oak},\text{develop_roots})\)
  • \(\mathrm{End}(h,\text{flourishing})\), \(\mathrm{Means}(\text{flourishing},\text{seek_truth})\)

From NL1:

  • \(\Box_a,\text{develop_roots}\)
    By reflexivity for non-free beings, \(\text{develop_roots}\) follows in the normal case (alethic “must”).
  • \(\Box_h,\text{seek_truth}\)
    But no T for free beings: it does not follow that \(h\) seeks truth. It’s an “ought.”

Same modal skeleton; different upshot because \(h\) is free.


7) What you get “for free” with this design

  • A single formal connective \(\Box_x\) that covers both “must” and “ought.”
  • A clean explanation of why natural law looks “descriptive” in biology/physics but “normative” in ethics: freedom is the switch.
  • A unified account of deviation (impairment vs wrongdoing) as failure to realize natural modal requirements.

If you want to push it further, the next natural move is to add a ranking (a “better-than” ordering) over \(R_x\)-accessible worlds for free agents (à la preference/ideality semantics), so \(\Box_x\) becomes “true in all best \(x\)-realizations of nature,” while for non-free agents it remains “true in all nature-compatible worlds.” That gives you a very natural-law-ish story about prudence, conflict of goods, and exception handling without changing the basic modal parallel.

Wednesday, January 21, 2026

Summary of Vangelov et al 2026 paper on fentanyl

The prompt was asking for a summary of this paper. The prompt contained the full text, hence it is not included to avoid infringement.

Here’s the paper’s core argument and evidence, in a detailed, “what did they do + what did they find + what does it mean” way.

What question they’re trying to answer

US fentanyl overdose deaths rose for ~15 years, then unexpectedly started dropping sharply in mid-2023. The authors ask: could a fentanyl supply shock (a major disruption in supply) explain a substantial part of that decline? They argue this is hard to prove directly because trafficking networks are secretive, so they triangulate from multiple indirect indicators.

The headline pattern they’re explaining

  • US synthetic-opioid overdose deaths (driven mostly by fentanyl) peaked at ~76,000 in 2023.
  • The trend reversed in mid-2023 and by end-2024 the annualized rate was down by over a third (their cited CDC reporting).
  • They claim the timing and cross-indicator consistency fits a major market disruption rather than only gradual improvements in treatment/harm reduction.

Why “supply shocks” are plausible in principle

They frame fentanyl as part of a broader history where big supply changes have caused big harm changes:

  • Upward shocks: prescription opioid overavailability (late 1990s), fentanyl’s entry into illicit supply (~2014).
  • Downward shocks: Australia’s “heroin drought” (2001) followed by ~60% drop in opioid overdose mortality.
  • Targeted scheduling: China’s control of carfentanil (2017) preceded drops in seizures/deaths where it was common.
  • Precursor controls: pseudoephedrine restrictions briefly constrained meth availability/harm.

So, the “market can swing fast” premise is established.


Evidence stream 1: “Conventional” supply indicators in the US

1) Purity data (DEA)

They use DEA’s monthly estimates (2019–Oct 2024) for average purity of seized fentanyl, split into powder vs pills, and compare it with monthly overdose death rates.

Key patterns they highlight:

  • Powder purity: rose sharply in 2022; peaked around ~25% by weight (Mar–Jul 2023); then fell by more than half, reaching about ~11% by end-2024.
  • Pill purity: also declined, but later and less—down by about one-third to roughly ~1.5%.

Interpretation they push:

  • Dealers often respond to scarcity not mainly by raising prices, but by diluting product (“shrinkflation”), which can reduce overdose risk if users end up exposed to less fentanyl per use.

They also report correlations across the full monthly series (Jan 2019–Oct 2024):

  • Synthetic-opioid overdose death rate correlated with pill purity: r = 0.62 (95% CI 0.44–0.74)
  • …and with powder purity: r = 0.37 (95% CI 0.15–0.56)

Their takeaway: purity and deaths turned down at about the same time, and are meaningfully correlated, consistent with a supply-side shift that changed potency exposure.

2) Seizure counts (NFLIS)

They treat the number of fentanyl seizures/identifications as another supply proxy:

  • US fentanyl seizures peaked in the first half of 2023
  • Fell 15% in the second half of 2023
  • By the second half of 2024 were 37% below the peak

They acknowledge a classic ambiguity: seizures could fall if enforcement intensity drops even if supply doesn’t. But they argue that given strong public/political attention during this period, a real supply reduction is more plausible than a large enforcement pullback.


Evidence stream 2: An “unconventional” indicator—Reddit as a customer-side signal

Because it’s hard to survey buyers in real time, they mine Reddit discussions where users talk candidly about availability/quality.

What they did

  • Scraped posts containing “fentanyl” and slang/misspellings (e.g., “fetty”) across six subreddits:

    • r/fentanyl, r/heroin, r/opiates, r/meth, r/cocaine, r/mdma
  • Within that set, they tracked monthly mentions of “drought” and similar shortage terms from Jan 2021 to Jan 2025

  • They manually checked that “drought” references were actually about fentanyl availability (not unrelated uses).

What they found

  • A first notable “drought” mention peak in July 2023
  • A much larger spike starting late 2023 that continued until subreddit moderation intervened
  • In Jan 2024, r/fentanyl’s moderator temporarily banned drought-related posts (concern about violating platform rules)
  • By July 2024, drought mentions rose again well above baseline and stayed elevated through end-2024

Their interpretation: discussions of shortages begin mid-2023, lining up with the beginning of the mortality decline, and persist into 2024—consistent with an extended disruption rather than a brief blip.


Evidence stream 3: Canada as a “supply chain comparator” to locate the shock’s source

This is their most “detective work” section: if both the US and Canada show downturns at similar times, it could hint the disruption is upstream (e.g., precursor chemicals), not only Mexico-specific actions.

Their premise about supply chains

They describe a “widely held view”:

  • Both countries depend on precursor chemicals largely sourced from China.
  • The US market: much fentanyl is synthesized in Mexico.
  • Canada: more synthesis is believed to occur domestically from imported precursors.
  • Cross-border US-Canada fentanyl flow is believed to be small relative to US-Mexico and Canadian domestic production.

So:

  • If the disruption is precursors, both countries could get hit around the same time.
  • If the disruption is mainly US/Mexico enforcement or Mexican producer dynamics, Canada should be less affected (or affected differently/timing mismatch).

What Canadian indicators show

Canada doesn’t publish national fentanyl-specific deaths monthly, but they use quarterly indicators where fentanyl dominates:

  • Quarterly opioid deaths (with >80% fentanyl-related): start declining in Q3 2023

  • Similar declines in:

    • EMS responses to suspected opioid poisonings
    • Opioid-related hospitalizations
    • Opioid poisoning ED visits

Supply-side Canadian lab signals are messier:

  • Average purity of analyzed fentanyl powder didn’t drop until late 2024, but became more volatile starting early–mid 2023.
  • Identifications of fentanyl in lab-assayed samples fell through 2021–2024, but was offset by increases in fentanyl analogs—a shift they say is not seen in US NFLIS patterns.

British Columbia (BC) as a special case

BC is singled out because it was hit early and plays a big role in Canada’s fentanyl context:

  • BC overdoses dipped in Aug–Sep 2023
  • But didn’t fall sharply until Oct 2024 (later than the national “start declining” signal)

Their inference from US–Canada comparison

  • Both countries’ overdose indicators begin falling around mid-2023, which they argue fits an upstream disruption.
  • But the way the markets “adapt” differs (Canada shows more analog substitution), suggesting the markets are distinct yet potentially constrained by a common bottleneck.

What they think caused the disruption (and how confident they are)

They stop short of claiming proof, but propose a leading candidate: Chinese actions that tightened scrutiny and control of precursor production/export, plus enforcement against online advertising/marketplaces.

Pieces they cite as consistent with this:

  • DEA’s 2025 National Drug Threat Assessment language noting declining purity in 2024 and reporting that Mexico-based producers had difficulty obtaining key precursors, and that some China-based suppliers were wary due to increased controls tied to UN treaty updates.

  • Reported Chinese actions in late 2023 and 2024:

    • A November 2023 notice warning about selling substances usable for drug manufacture
    • Increased enforcement activity against synthetic drug/precursor suppliers
    • Claims by June 2024 of taking down large volumes of ads and multiple platforms
    • A Biden–Xi meeting in Nov 2023 linked to increased cooperation

They also discuss the geopolitical logic: the US bears huge overdose costs; China’s domestic opioid burden is small, so China may have leverage to act at relatively low domestic cost.

They acknowledge alternative explanations (including “maybe US/Mexico interventions hit the US supply while something separate hit Canada”), but argue the parallel timing makes an upstream story plausible.


Policy implications they draw

They caution against everyone claiming credit (“success has many fathers”), and emphasize that if supply disruption played a big role, it changes how you interpret “what worked.”

Three big implications if it was a supply shock:

  1. Supply control might matter without mass street-level arrests

    • They stress there wasn’t a visible surge of retail arrests like in earlier US drug wars, and that’s “heartening” because street enforcement can drive incarceration and racial disparities without reliably raising prices or reducing availability.
  2. The good news may be temporary

    • Trafficking organizations often adapt to shocks (they analogize to meth precursor controls).
    • Possible adaptations: bigger inventories, hardened logistics, alternative precursors/routes.
  3. Use the “drought window” to reduce demand

    • Scale prevention and treatment with evidence for lowering demand, while supply is constrained, because incentives to restore supply persist.

And if China really contributed materially:

  • Diplomacy and international cooperation could have surprisingly high payoff.
  • Engage other potential precursor-producing countries, especially India, which they note is a growing concern in enforcement discussions.

Limitations they explicitly flag

They’re pretty direct that this is an inference-heavy, nonexperimental analysis:

  • No randomization / causal identification: coincident internal changes in US/Canada could theoretically explain the patterns.
  • Purity data representativeness: seizure purity isn’t necessarily retail purity; powder samples may be more wholesale. Shifts in the mix of sample types over time could bias average purity trends.
  • COVID retreat as alternative: they consider whether waning COVID reduced overdoses. They argue timing is off—ODD decline begins in 2023, well after the last major COVID mortality peak in early 2022 (they cite a week in Jan 2022 and a large decline over the next three months).
  • China inference is speculative because of limited transparency and episodic reporting.
  • Data gaps: they call for more systematic real-time monitoring of drug supply chains, including better purity tracking and structured social media surveillance.

Bottom line of the paper

They don’t claim a smoking gun, but argue that multiple independent indicators point in the same direction:

  • US purity down + deaths down + seizures down, starting mid-2023
  • Reddit users talking about shortages beginning mid-2023 and continuing into 2024
  • Canada’s opioid death indicators also turning down around mid-2023 (with some regional timing differences), which supports the idea of an upstream disruption (e.g., precursor constraints)

So their answer is essentially: yes, the fentanyl trade likely experienced a supply disruption, and that disruption could plausibly explain a meaningful portion of the sharp overdose-death decline beginning mid/late-2023.

If you want, I can also:

  • extract the paper’s implied causal chain as a simple diagram (precursors → purity/availability → dose exposure → deaths), or
  • list what new data would most strongly confirm vs refute the supply-shock hypothesis.