Tuesday, August 26, 2025

Sum and product puzzle

Mr. Puzzle: I choose two natural numbers greater than 1. I will tell the sum of the numbers only to Mr. Sum, and their product only to Mr. Product.
He tells them.
Mr. Product: I do not know the numbers.
Mr. Sum: I knew you didn’t.
Mr. Product: But now I know!
Mr. Sum: So do I!

What can be the numbers if they are not greater than 100?

4 and 13.

Why (short version):

  • Mr. Product doesn’t know ⇒ the product has more than one factorization in 2..100 (so not a prime, not a prime square like $49=7\cdot7$, etc.).
  • Mr. Sum “knew” that ⇒ for every split of his sum $S$ into two numbers $\ge 2$, the product would still be ambiguous. That forces $S$ to be one of the sums that cannot be written as prime + prime (within 2..100). Those are $\{11,17,23,27,29,35,37,41,47,53\}$.
  • Mr. Product now knows ⇒ among his product’s factor pairs, exactly one has a sum from that set. For $52$: $52=2\cdot26$ (sum 28, not in the set) or $52=4\cdot13$ (sum 17, in the set). So Product deduces $4$ and $13$.
  • Mr. Sum now knows ⇒ with $S=17$, the splits are $(2,15),(3,14),(4,13),(5,12),(6,11),(7,10),(8,9)$. Only $(4,13)$ has a product (52) that would let Product deduce uniquely at the previous step; the others (e.g., $30=2\cdot15=3\cdot10=5\cdot6$) still leave Product with multiple “good” sums.

Hence the unique pair ≤100 is (4, 13).

Reasonable doubt algorithm

I’m thinking of a formal model of someone reasoning about whether a defendant is “beyond reasonable doubt”. It involves the following notions:

Countermodel: A possible world that fits all the evidence we have, but in which the defendant is not guilty.

Living Eligible Reasoners (LER): All living people who are eligible to reason about the problem, i.e. would not be disqualified due to their young age, or their mental health condition, etc.

Probability Behavioral Threshold (PBT): For a given person p and a given possible world w, the threshold of probability, accorded by p to w, above which p is moved to actually perform the actions corresponding to raising the doubt as a serious possibility to the jury, assuming for simplicity that there is such a threshold, and that everyone has too much civic duty to get skittish.

Reasonable Doubt Algorithm (RDA): For each LER_i and for each countermodel_j, imagine a situation S in which P(countermodel_j) > PBT_LER_i, so that LER_i raises countermodel_j as a doubt.

  1. In S, would all reasonable people agree that LER_i is a reasonable person acting reasonably?
  2. If an arbitrary different LER, call them LER_d, thinks LER_i must be unreasonable in S, is it reasonable for LER_d to label LER_i as unreasonable? (If everyone who is a reasonable person, with a reasonable caution against being moved by an unreasonable prejudice against someone with different beliefs, would avoid labelling LER_i as unreasonable in S, then it is not reasonable for LER_d to label LER_i as unreasonable in S.)
    If there exists any situation S in which the answer to both questions is “Yes”, then there is a reasonable doubt against the defendant.

RDA may seem extremely unwieldy, but each person in a jury only has a limited life experience and reasoning power, so they only have a certain number of countermodels that they consider plausible enough to not rule out anyone who raises them (even their most trusted friend) as acting unreasonably if they raise them; and they only have a limited number of imaginable LERs. For instance, an LER who lives in a rural part of India and has different cultural background assumptions may be too difficult for a WEIRD person to imagine, so they won’t even try, since their imagination would be too inaccurate to be useful. In practice people do come to a decision, and what goes through their head is probably some heuristic about RDA. Evaluations of reasonableness are not fully understood but may be modelled with supervaluationist semantics of vagueness. For illustration we may picture the reasoner looking at a table or matrix where the rows are admissible countermodels, the columns are imaginable LERs, and looking for a value of the reasonableness of the countermodel being raised by the LER which is above the supervaluationist reasonableness threshold.

Please write out a better formalized version of this formal model, written as an introduction to the RDA model for someone who has not read my explanation.

An Introduction to the RDA Model (Reasonable-Doubt via Countermodel–Reasoner Assessment)

This note gives a compact, formal version of your idea so a new reader can work with it.

1) Ingredients

  • Evidence. Let $E$ be the total admissible evidence.

  • Worlds and hypotheses. Let $W$ be a set of possible worlds; $w \models E$ means $w$ fits the evidence. Let $G(w)\in\{\text{guilty},\text{not-guilty}\}$. A countermodel is a hypothesis $H\subseteq \{w\in W: w\models E\ \land\ G(w)=\text{not-guilty}\}$. Think of $H$ as a structured “story type,” not a single world.

  • Eligible reasoners. Let $\mathcal L$ be the set of Living Eligible Reasoners (LERs) (legally/competently eligible persons). For a particular juror $J$, let $\mathcal I_J\subseteq\mathcal L$ be the subset of imaginable LERs (those $J$ can model with enough fidelity to evaluate).

  • Credences and thresholds. Each $r\in\mathcal L$ has a posterior $P_r(\cdot\mid E)$ on hypotheses and a Probability Behavioral Threshold $T_r: \mathcal P(W)\to[0,1]$ with the action rule

    $$ \textbf{Raise}(r,H) \ \text{iff}\ P_r(H\mid E)\ >\ T_r(H). $$

    (If desired, take $T_r$ to be a constant $t_r$ across $H$.)

2) Scenarios

For any pair $(r,H)$ with $H$ a countermodel, define a scenario

$$ S(r,H) := \langle E,\ r,\ H,\ P_r(\cdot\mid E),\ T_r\rangle $$

in which $r$ would raise $H$ (i.e., $P_r(H\mid E)>T_r(H)$). Intuitively, $S(r,H)$ is the deliberative situation “as if $r$ were on this case with this evidence.”

3) Reasonableness as a vague predicate (supervaluationist layer)

Let $\Pi$ be the set of admissible precisifications of the vague predicate “is (acting) reasonable.” Each $\pi\in\Pi$ assigns two crisp predicates:

  • $\mathrm{Reasonable}_\pi(r;S)\in\{0,1\}$: in scenario $S$, $r$ is a reasonable person acting reasonably.
  • $\mathrm{ReasonableLabel}_\pi(d\!\to\!\text{“}r\text{ is unreasonable”};S)\in\{0,1\}$: in $S$, it is reasonable for $d$ to label $r$ unreasonable.

Aggregate these via supervaluation:

  • Super-truth: $\mathrm{R}^\ast(r;S)=1$ iff $\mathrm{Reasonable}_\pi(r;S)=1$ for all $\pi\in\Pi$.
  • Super-permission to label: $\mathrm{RL}^\ast(d\!\to\!\text{“}r\text{ unreasonable”};S)=1$ iff $\mathrm{ReasonableLabel}_\pi(\cdot)=1$ for all $\pi\in\Pi$.

Optionally, replace super-truth with a thresholded aggregator: pick $\alpha\in(0.5,1]$ and set

$$ \mathrm{R}^{\alpha}(r;S)=1 \ \text{iff}\ \frac{1}{|\Pi|}\sum_{\pi\in\Pi}\mathrm{Reasonable}_\pi(r;S)\ \ge \alpha $$

(and analogously for $\mathrm{RL}^\alpha$). Super-truth is the special case $\alpha=1$.

4) No-Reasonable-Rejection (second-order safeguard)

A central stability idea is that reasonable doubt should not depend on an unreasonable intolerance of others’ reasoning styles. For $J$’s imaginable peer set $\mathcal I_J$:

$$ \mathrm{NoReject}^\alpha_J(r;S)\quad\text{iff}\quad \forall d\in \mathcal I_J,\ \mathrm{RL}^{\alpha}(d\!\to\!\text{“}r\text{ unreasonable”};S)=0. $$

So even if some $d$ would dismiss $r$, that dismissal must itself fail to be (super-)reasonable.

5) The RDA decision rule

Fix a juror $J$, an aggregator level $\alpha$ (default $=1$, i.e., super-truth), and a reasonableness acceptance threshold $\tau\in\{0,1\}$ (default $\tau=1$). $J$ declares the charge not proven beyond reasonable doubt iff

$$ \exists H\ \text{countermodel},\ \exists r\in \mathcal I_J \quad\text{s.t.}\quad \begin{cases} P_r(H\mid E) > T_r(H) & \text{(r would raise H)}\\[2pt] \mathrm{R}^{\alpha}(r; S(r,H)) \ \ge \ \tau & \text{(raising is reasonable)}\\[2pt] \mathrm{NoReject}^{\alpha}_J(r; S(r,H)) & \text{(robust to reasonable dissent).} \end{cases} $$

Equivalently: if there exists an imaginable eligible person who would raise a concrete exculpatory story $H$, whose doing so is (super-)reasonable, and whom no imaginable eligible person could (super-)reasonably condemn for doing so, then reasonable doubt exists. Conviction requires the negation of that existential condition.

6) Finite “matrix” implementation (practical juror heuristic)

Actual jurors consider finite sets. Let $ \mathcal C_J=\{H_1,\dots,H_m\}$ be $J$’s admissible countermodels and $ \mathcal I_J=\{r_1,\dots,r_n\}$ the imaginable LERs. Define the reasonableness matrix $M\in[0,1]^{m\times n}$ (under your chosen aggregator) by

$$ M_{j,i} \ :=\ \mathrm{R}^{\alpha}(r_i; S(r_i,H_j)). $$

For each cell, also track rejection-stability

$$ S_{j,i} \ :=\ \mathbf{1}\big(\mathrm{NoReject}^{\alpha}_J(r_i; S(r_i,H_j))\big), $$

and the actionability flag

$$ A_{j,i} \ :=\ \mathbf{1}\big(P_{r_i}(H_j\mid E) > T_{r_i}(H_j)\big). $$

Then RDA says reasonable doubt exists iff there is some $(j,i)$ with $A_{j,i}=1$, $M_{j,i}\ge\tau$, and $S_{j,i}=1$.

This exactly matches the “look across rows (countermodels) and columns (LERs) and search for an above-threshold entry” picture.

7) Notes, properties, and variants

  • Monotonicity in evidence. If $E\subseteq E'$ (i.e., you add evidence), countermodels only shrink: for fixed $\mathcal I_J$, it becomes harder to satisfy the RDA existential.
  • Sensitivity to imagination. Broadening $\mathcal I_J$ (more diverse, still-eligible reasoners that $J$ can model) weakly increases the chance of reasonable doubt, both by adding potential raisers and by tightening the No-Reject condition.
  • Threshold design. $T_r(H)$ can encode civic duty, speaking costs, aversion to frivolity, etc. Lower $T_r$ makes raising easier; RDA remains conservative because of the second-order No-Reject check.
  • Supervaluation knobs. – Set $\alpha=1$ for a maximally conservative (unanimity-across-precisifications) reading of “reasonable.” – Use $\alpha<1$ to permit borderline but sufficiently supported cases to count as reasonable. – You may also place the $\alpha$ threshold on No-Reject only (keeping $\alpha=1$ for $\mathrm{R}$).
  • One-world vs. hypothesis granularity. If preferred, take countermodels as single worlds; then replace $P_r(H)$ with $P_r(\{w\})$. The hypothesis-set version better matches legal narratives.
  • Symmetry/peerhood. You can restrict $d$ in No-Reject to a vetted “reasonable-peer subset” of $\mathcal I_J$ (e.g., domain-relevant competence) without changing the basic form.
  • Normative vs. descriptive. The rule is normative (what counts as reasonable doubt); actual juror cognition can be modeled as heuristics that approximate the matrix search.

This formulation isolates (i) evidential compatibility (countermodels), (ii) actionability (would a real, eligible person raise it?), (iii) first-order reasonableness of raising, and (iv) second-order stability against reasonable condemnation. Conviction is permitted only when every admissible, imaginable countermodel–raiser pair fails at least one of those gates.

Some people believe that reasonable doubt should be modeled simply as a probability threshold T such that, if P(guilty|evidence) > T, then the defendant is guilty beyond reasonable doubt. Comparing this simple-threshold model with the RDA model may be fruitful as a way to show why people recoil at this idea. Make such a comparison, noting how much simplification must be introduced into the RDA model to parallel the simple-threshold model.

Here’s a clean comparison that shows what the simple “probability-threshold” view has to assume (or delete) from the RDA model to make the two line up—and why many people bristle at the threshold view.

The two targets

  • Simple threshold model (STM). Pick a number $T\in(0,1)$. If a juror’s $P(\text{guilty}\mid E) > T$, return “guilty beyond reasonable doubt,” else “not guilty.”

  • RDA (from your earlier spec). There is reasonable doubt iff there exists a countermodel $H$ (a concrete not-guilty “story type”) and an imaginable eligible reasoner $r$ such that (i) $r$ would raise $H$ (their posterior on $H$ exceeds their probability-behavioral threshold), (ii) doing so is reasonable (under a supervaluationist reading of “reasonable person acting reasonably”), and (iii) it is not reasonable for any imaginable eligible peer to dismiss $r$ as unreasonable for raising $H$ (the “no reasonable rejection” safeguard).

How to collapse RDA into STM (and how much you must simplify)

To make RDA behave like STM, you have to successively strip away its structure until only a single scalar remains. Here is a minimal set of simplifying moves:

  1. Erase interpersonal heterogeneity. Replace the plurality of Living Eligible Reasoners with a single representative reasoner $r^\$ whose posterior $P^\(\cdot\mid E)$ everyone shares (common priors, common likelihoods, common updates).

  2. Flatten actionability. Make the probability behavioral threshold constant and content-independent: $T_{r^\*}(H) \equiv \varepsilon$ for all $H$. (In RDA this threshold governs speaking up; here we repurpose it to line up with a verdict cutoff.)

  3. Trivialize “reasonableness.” Collapse the vague predicate (“reasonable person acting reasonably”) and its supervaluationist layer to a crisp rule: raising $H$ is reasonable iff $P^\(H\mid E)\ge \varepsilon$.* (Equivalently: choose one precisification and set the acceptance level $\alpha=1$ so that reasonableness = meets the numeric cutoff.)

  4. Vacuate second-order scrutiny. Since there is only $r^\*$, the “can a reasonable peer label $r$ unreasonable?” check is automatically satisfied and drops out.

  5. Permit a maximally disjunctive countermodel. Declare the set $H_{\lnot G} := \{w:\text{not guilty}\}$ to be an admissible countermodel. Then $P^\(H_{\lnot G}\mid E)=1-P^\(\text{guilty}\mid E)$.

  6. Identify cutoffs. Set $\varepsilon = 1-T$.

Result of the reductions. RDA now says: There is reasonable doubt iff $\exists H$ with $P^\(H\mid E)>\varepsilon$.* Because $H_{\lnot G}$ is admissible, this is equivalent to

$$ P^\*(\text{guilty}\mid E) < T, $$

which is just the negation of the STM conviction rule. Thus, STM is the special case of RDA obtained by (1)–(6).

Takeaway: to get the threshold picture, you must (i) force a single shared posterior, (ii) replace “reasonableness” with a numeric cutoff, (iii) delete the second-order check against unreasonable intolerance, and (iv) allow “not guilty, somehow” as a legitimate countermodel.

What gets lost in the simplification (and why people recoil)

  1. Who is judging—and the respect owed to reasonable dissent. STM is silent about which competent people would speak up and whether it is reasonable to dismiss them. RDA bakes in a safeguard: even if most peers would convict, a reasonable dissenter with a reasonable countermodel blocks conviction. Many find this morally attractive in criminal law.

  2. Narrative adequacy vs. bare probability. STM needs no story—only a number. RDA privileges articulable alternatives: an exculpatory hypothesis that a reasonable person could responsibly present. People often dislike “0.90 means guilty” precisely because it treats a black-box number as sufficient, without asking what the 10% is made of.

  3. Second-order fairness. In RDA, you cannot convict merely by calling the dissenter “unreasonable”; that labeling act itself must be reasonable. STM has no such meta-norm, so socially dominant priors or prejudices can win just by being numerically entrenched.

  4. Action vs. belief. RDA distinguishes having a small credence in a countermodel from being moved to act (raise it). STM fuses everything into a single verdict threshold. Many people think criminal standards should track the ethics of acting under uncertainty, not only posterior levels.

  5. Heterogeneity and minority epistemics. RDA lets different competence profiles matter (e.g., a lab-savvy LER seeing a 2% testing-protocol failure). STM, by construction, averages such insight into one number or ignores it entirely.

  6. Vagueness handled as vagueness. “Reasonable” is vague; RDA treats it with supervaluation (or another explicit aggregator). STM chases the comfort of a single number by fiat, which can feel like pseudo-precision.

  7. Asymmetric presumption. RDA’s existential form (“∃ a reasonable raiser of a reasonable countermodel”) naturally encodes the presumption of innocence. STM has to stipulate an asymmetric $T$ (e.g., .95) and still sounds like, “we tolerate a 1 in 20 risk of wrongful conviction,” which many find morally jarring.

Illustrative contrasts

  • Respectable outlier. A credible forensic path $H$ with $P(H\mid E)=0.02$. – STM with $T=0.95$: convict (0.98 > 0.95). – RDA: acquit if raising this 2% path is something a reasonable expert would do and no reasonable peer could justifiably dismiss them. This aligns with “better that ten guilty go free…”

  • Diffuse doubt. Ten disjoint $H_1,\dots,H_{10}$ each at 1%. – STM with $T=0.90$: acquit (total $P(\lnot G)=0.10$). – RDA (without step 5 above): if jurors demand specific alternatives and treat a big disjunction as unreasonable to raise, they might still convict. This shows that insisting on specific narratives is an extra normative choice RDA can represent but STM cannot.

  • Peer-group polarization. Two camps of LERs disagree on a countermodel’s import. – STM: whichever camp controls the single $P(\cdot)$ or the chosen $T$ decides. – RDA: conviction must survive the second-order check—if it is not reasonable to label the dissenter unreasonable, you cannot convict.

Side-by-side summary

Dimension STM (Probability Threshold) RDA (Countermodel–Reasoner)
Unit of evaluation Scalar $P(\text{guilty}\mid E)$ Pairs $(\text{countermodel }H,\ \text{reasoner }r)$
Decision form Global cutoff $T$ Existential: ∃ $H,r$ passing three gates
Specificity None required Rewards specific, articulable alternatives
Disagreement Ignored Second-order “no reasonable rejection” check
Heterogeneity Suppressed Central (different $P_r$, $T_r$, competencies)
Vagueness of “reasonable” Hidden in $T$ Explicit (supervaluation / $\alpha$-aggregator)
Actionability None (belief → verdict) Distinguishes “would raise” from mere belief
Fit to presumption of innocence By choice of high $T$ Built-in via ∃-form

Bottom line

  • Equivalence requires heavy surgery on RDA: one shared posterior, one numeric cutoff that is “reasonableness,” no dissent check, and permission to raise the blanket disjunction “not guilty.”
  • That surgery removes exactly the features people care about in a criminal standard—respect for reasonable dissent, the demand for concrete alternative stories, the ethics of action under uncertainty, and the acknowledgement that “reasonable” is not a single number.

That is why many recoil at “just pick $T$”: it feels like replacing a social-normative safeguard with a solitary dial.

ℝ² vs ℂ

Similarities and differences between ℝ² and ℂ

Quick answer — same space, different structure

At the level of points and topology, $\mathbb{R}^2$ and $\mathbb{C}$ are the same: there is a bijection

$$ \Phi:\mathbb{R}^2\to\mathbb{C},\qquad \Phi(x,y)=x+iy, $$

which is a homeomorphism and an isometry if you use the Euclidean norm on $\mathbb{R}^2$ and the modulus on $\mathbb{C}$. So they share the same geometry (distance, open sets, continuity), the same dimension as real vector spaces (dimension $2$), etc.

But they differ in extra algebraic structure and the consequences of that structure.


Similarities

  • As sets / topological spaces / metric spaces: $\mathbb{R}^2$ ≅ $\mathbb{C}$ (via $(x,y)\mapsto x+iy$). Same Euclidean metric: $\|(x,y)\|=\sqrt{x^2+y^2}=|x+iy|$.
  • Real vector space: Both are real vector spaces of dimension 2. Basis in $\mathbb{C}$ (over $\mathbb{R}$) is $\{1,i\}$.
  • Linear algebra / inner product: Using the usual dot product on $\mathbb{R}^2$ and $\langle z,w\rangle=\Re(z\overline w)$ on $\mathbb{C}$ they represent the same Euclidean inner product.
  • Orientation and area: Same notion of oriented area; multiplication by a complex number $re^{i\theta}$ scales area by $r^2$ and preserves orientation.

Key differences (what makes $\mathbb{C}$ special)

  1. Field vs plain vector space

    • $\mathbb{C}$ is a field: you can multiply complex numbers and divide by nonzero ones.
    • $\mathbb{R}^2$ as usually presented has no canonical multiplication. You can define a multiplication to make it a field isomorphic to $\mathbb{C}$, but $\mathbb{R}^2$ with only coordinate-wise structure is not a field.
  2. Complex multiplication = rotations + scalings

    • Multiplication by $a+bi$ corresponds to the linear map on $\mathbb{R}^2$ with matrix

      $$ \begin{pmatrix} a & -b\\[2pt] b & a\end{pmatrix}, $$

      i.e. a composition of rotation and dilation. This structure is not present in a raw $\mathbb{R}^2$ unless you pick this complex multiplication.

  3. Scalar fields

    • $\mathbb{R}^2$ is a 2-dimensional vector space over $\mathbb{R}$.
    • $\mathbb{C}$ is a 1-dimensional vector space over $\mathbb{C}$ and a 2-dimensional vector space over $\mathbb{R}$. This difference matters for linear maps: $\mathbb{C}$-linear maps are much more restrictive than $\mathbb{R}$-linear maps.
  4. Complex linearity vs real linearity

    • A map $T:\mathbb{C}\to\mathbb{C}$ that is $\mathbb{C}$-linear must satisfy $T(i z)=iT(z)$. In $\mathbb{R}^2$ language those are exactly the real-linear maps with matrices of the form above (complex-scalar matrices).
    • There are many more $\mathbb{R}$-linear maps on $\mathbb{R}^2$ than $\mathbb{C}$-linear maps on $\mathbb{C}$. Example: complex conjugation $z\mapsto\overline z$ is $\mathbb{R}$-linear but not $\mathbb{C}$-linear.
  5. Differentiability / holomorphicity

    • If you view functions $f:\mathbb{R}^2\to\mathbb{R}^2$ the usual (real) differentiability is much weaker than complex differentiability. A complex function $f:\mathbb{C}\to\mathbb{C}$ being holomorphic requires the Cauchy–Riemann equations — a very rigid condition. Holomorphic ⇒ infinitely differentiable and analytic; real differentiable need not imply that.
  6. Algebraic closure

    • $\mathbb{C}$ is algebraically closed: every nonconstant polynomial (with complex coefficients) has a root in $\mathbb{C}$.
    • $\mathbb{R}^2$ (as a plain 2D real vector space) has no meaning of algebraic closure unless you impose multiplication; with the usual identification $\mathbb{R}^2\cong\mathbb{C}$, that property belongs to $\mathbb{C}$.
  7. Order structure

    • $\mathbb{R}$ is an ordered field; $\mathbb{C}$ cannot be given a field order compatible with its operations. $\mathbb{R}^2$ has no natural total order compatible with vector-space structure.
  8. Unique complex structure (up to sign)

    • A “complex structure” on $\mathbb{R}^2$ is a linear map $J:\mathbb{R}^2\to\mathbb{R}^2$ with $J^2=-I$. Choosing such $J$ identifies $\mathbb{R}^2$ with $\mathbb{C}$. All such $J$ that are compatible with the Euclidean metric are rotations by $90^\circ$ (and its negative) — so the complex structure is essentially unique (two choices corresponding to $i$ vs $-i$).

Useful formulas / examples

  • Identification: $(x,y)\leftrightarrow x+iy$.

  • Addition: $(x,y)+(u,v)=(x+u,y+v)$ corresponds to $(x+iy)+(u+iv)$.

  • Multiplication (via identification):

    $$ (x,y)\cdot(u,v)=(xu-yv,\; xv + yu). $$

  • Matrix for multiplication by $a+bi$:

    $$ M(a,b)=\begin{pmatrix} a & -b\\ b & a\end{pmatrix}. $$

  • Modulus / norm: $|x+iy|=\sqrt{x^2+y^2}$.


One-sentence summary

$\mathbb{R}^2$ and $\mathbb{C}$ are the same as sets and as real vector spaces / metric spaces, but $\mathbb{C}$ carries extra algebraic (field) and analytic structure (complex multiplication, complex-linear maps, holomorphicity) that makes it strictly richer than the plain 2-dimensional real plane.

Would you like a short table comparing properties side-by-side, or examples showing how complex differentiability (Cauchy–Riemann) restricts a real map?

Largest freshwater animal

largest freshwater animal

The largest freshwater animal in the world is generally considered to be the giant freshwater stingray (Urogymnus polylepis).

Size

  • It can reach up to 5 meters (16 feet) in length, including the tail.
  • Weighs as much as 600–800 kg (1,300–1,800 lbs).
  • Native to rivers in Southeast Asia, such as the Mekong and Chao Phraya.

Other Contenders

Depending on how “largest” is defined (length vs. weight), there are other rivals:

  • Beluga sturgeon (Huso huso): Found in the Caspian and Black Sea basins; can exceed 7 meters (23 feet) and weigh over 1,500 kg (3,300 lbs). However, it spends much of its life in brackish waters, not strictly freshwater.
  • Mekong giant catfish (Pangasianodon gigas): Native to the Mekong River, it can grow up to 3 meters (10 feet) and weigh up to 300 kg (660 lbs).

👉 If we’re strict about freshwater-only species, the giant freshwater stingray holds the record. 👉 If we include fish that migrate between freshwater and brackish/sea environments, the beluga sturgeon can be even larger.

Would you like me to make you a size comparison chart of these freshwater giants?

Eudaimonia cost

Approximately how much money does eudaimonia require?

Short answer: there’s no single dollar figure — eudaimonia (human flourishing) mostly needs enough money to remove insecurity and buy you time and agency, not infinite wealth. That said, here are practical, approximate anchors you can use.

Rough anchors (annual income / nest-egg view)

  • Basic security (cover food, housing, healthcare, transport) — depends a lot on country and city.

    • In many parts of the U.S., that’s roughly $20,000–$40,000 / year for a single person; in expensive metro areas it’s higher.
  • “Comfortable” living (less financial stress, modest extras)~$50,000–$120,000 / year, depending on location and family size.

  • The frequently-cited “happiness plateau” from well-being research: classic studies found emotional well-being rises with income up to about $75,000 / year (older figure); more recent work puts the range somewhat higher (often quoted $90k–$100k / year for certain measures of life evaluation). These are guides, not magic thresholds.

If you’re thinking in terms of a retirement / freedom nest egg (safe-withdrawal rule)

People often use the “25× annual spending” rule (the 4% rule). I’ll show the math digit-by-digit:

  • To support $75,000 / year:

    1. 75,000 × 20 = 1,500,000.
    2. 75,000 × 5 = 375,000.
    3. Add: 1,500,000 + 375,000 = 1,875,000. So ~$1,875,000 in savings.
  • To support $100,000 / year:

    1. 100,000 × 25 = (100,000 × 20) + (100,000 × 5) = 2,000,000 + 500,000 = 2,500,000.
  • To support $40,000 / year:

    1. 40,000 × 25 = (40,000 × 20) + (40,000 × 5) = 800,000 + 200,000 = 1,000,000.

Key point (philosophical & practical)

Eudaimonia = flourishing through virtue, meaningful activity, relationships, autonomy. Money helps by removing scarcity and buying time/choices, but past the point of security and reasonable comfort its marginal effect on deep flourishing drops. Most of the long-term gains to “flourishing” come from non-monetary investments: community, meaningful work, health, and time-control.

Quick, practical takeaway

Aim first to eliminate financial insecurity (an emergency fund + predictable income). After that, use money to buy time, health, experiences, and opportunities for meaningful engagement. If you want, tell me your country/city and whether you mean annual income or a retirement nest-egg, and I’ll give more tailored numbers (no need to answer if you prefer this general guide).

Handshaking lemma proof

Show that the number of vertices of odd degree in a graph is always even.

Proof (Handshaking lemma / parity argument)

Let $G=(V,E)$ be a finite graph. For each vertex $v\in V$ let $\deg(v)$ denote its degree. Two standard facts:

  1. Each edge contributes exactly $2$ to the total sum of degrees (one for each endpoint). Hence

$$ \sum_{v\in V}\deg(v)=2|E|, $$

so the total sum of degrees is even.

  1. Split the vertex set $V$ into $V_{\text{even}}$ (vertices of even degree) and $V_{\text{odd}}$ (vertices of odd degree). The sum of degrees over $V_{\text{even}}$ is even (sum of even numbers). Therefore the parity of the whole sum equals the parity of the sum over $V_{\text{odd}}$. But the sum of $k$ odd numbers has the same parity as $k$ (odd sum iff $k$ is odd). Thus

$$ \sum_{v\in V}\deg(v)\ \text{is even} \quad\Longrightarrow\quad |V_{\text{odd}}|\ \text{is even}. $$

So the number of vertices of odd degree must be even. ∎

Wednesday, August 20, 2025

Pedophile-romanticizing literature list

Besides "Death in Venice" and "Lolita", are there any great (widely renowned) literary works that romanticize pedophiles? I have heard some people criticize the Western literary tradition as having many such works among its great widely renowned literary fiction, but in order to fairly evaluate this claim I must look for more examples that would be cited

Short answer: yes—there are a number of widely studied/canonical works that critics often cite when arguing the Western canon has romanticized or aesthetically dignified adult–minor desire. Just note that many of these books are contested: some readers see them as critical indictments, others as normalization/romance. Here’s a compact, representative list (leaving out Death in Venice and Lolita as you asked):

  • Classical backbone of the canon (man–boy love idealized): Plato’s Symposium (and Phaedrus) present speeches that treat pederastic love—adult men with adolescent boys—as noble/educative; more broadly, Greek literature made such relationships a recurring theme. Histories and reference entries document how pederasty was socially acknowledged and celebrated in elite discourse, which shapes how those texts read today. (HistoryExtra, Oxford Research Encyclopedias)

  • Samuel Richardson, Pamela (1740): A hugely influential English novel whose 15-year-old heroine is relentlessly pursued by her wealthy employer and ultimately marries him—a plot long criticized for legitimizing coercion. (Encyclopedia Britannica)

  • Choderlos de Laclos, Les Liaisons dangereuses (1782): A foundational Enlightenment novel in which the libertine Valmont seduces Cécile de Volanges, who is about 15 and fresh from the convent—frequently cited as an elegant aestheticization of abuse. (Age noted in standard study guides and reference entries.) (SparkNotes, Encyclopedia Britannica)

  • André Gide, The Immoralist (1902): Canonical modernist novel (by a future Nobel laureate) that includes the narrator’s eroticized attention to adolescent boys, often discussed as romanticizing/normalizing his desires amid a self-liberation narrative. (Literary Theory and Criticism)

  • Vladimir Nabokov, The Enchanter (written 1939; Eng. trans. 1986): A compact precursor to Lolita told from a pedophile’s viewpoint; critics commonly group it with examples that aestheticize the predator’s subjectivity. (Los Angeles Times, Goodreads)

  • Penelope Fitzgerald, The Blue Flower (1995): National Book Critics Circle Award–winning novel about the Romantic poet Novalis’s rapturous attachment to Sophie von Kühn—twelve when he first falls for her—narrated with luminous tenderness that some readers find troubling. (Wikipedia, EBSCO)

  • Bernhard Schlink, The Reader (1995): International bestseller and widely taught; it frames the affair of a 36-year-old woman with a 15-year-old boy within a coming-of-age/memory story—often criticized as romantically toned even as it engages postwar guilt. (Wikipedia, Encyclopedia Britannica)

  • Gabriel García Márquez, Memories of My Melancholy Whores (2004): A ninety-year-old narrator “falls in love” with a sleeping 14-year-old girl; major reviews describe the book as a rhapsodic “love letter” that many readers see as romanticizing predation. (The New Yorker, Encyclopedia Britannica)

  • Alissa Nutting, Tampa (2013): A satirical, deliberately glossy inside-the-predator’s-mind portrait of a 26-year-old teacher grooming a 14-year-old boy; widely reviewed and frequently invoked in this debate. (The Guardian)

  • Often cited, but explicitly critical rather than romanticizing: Kate Elizabeth Russell, My Dark Vanessa (2020)—about a 15-year-old groomed by her teacher—was marketed and read as a #MeToo-era corrective; serious critics emphasized it is not a romance but an immersion in abuse and complicity. It still appears in these conversations because of how it interrogates the seductive myths. (The Atlantic, The Guardian)

A couple of framing notes

  • Terminology matters. Strictly speaking, pedophilia refers to attraction to pre-pubescent children; many literary cases (e.g., classical pederasty or 15–16-year-old “ingénues”) would be labeled hebephilia/ephebophilia today. Critics often use “pedophile” colloquially, but the distinction is part of scholarly debates about these texts. (Oxford Research Encyclopedias)
  • Reception is split. Some readers see these works as critiques of predation (or as historically contextual depictions); others argue that the elegance of the prose, the centering of the adult’s feelings, or the narrative “rewards” (e.g., marriage, exalted love) functionally romanticize it.

If you want, I can sort these into buckets—“clearly celebratory,” “ambiguous/contested,” and “explicitly critical”—or add more examples from specific periods (Victorian, modernist, etc.) for a fuller audit.

No need to reorder the list, I will research criticism of each of the works separately later. Continue to use chronological order as that is helpful to trace a historical evolution. Are there any more works besides those?

Yep—here are more often-cited examples (kept strictly chronological, still excluding Death in Venice and Lolita). Brief notes flag why critics bring them up; “romanticize” is debated title-by-title.

  • The Letters of Abelard and Héloïse (12th c.) — celebrated love letters between a famous teacher and his much younger pupil; many historians place Héloïse in her mid-teens when the affair began. (Christian History Institute, Encyclopedia Britannica)
  • Goethe, Faust Part I (1808) — Faust seduces Gretchen, explicitly said in the text to be “over fourteen.”
  • Colette, Claudine at School (1900) — a 15-year-old pupil entangled in erotic intrigues involving adult teachers; often discussed for its teacher–student dynamics. (Wikipedia)
  • Jun’ichirō Tanizaki, Naomi (1924) — a 28-year-old narrator grooms a 15-year-old café girl he “rescues” and remakes; the novel knowingly glamorizes the project. (Wikipedia)
  • Vladimir Nabokov, Laughter in the Dark (1932) — middle-aged man obsessed with a teenager (Margot is 16–17 in most summaries). (Wikipedia)
  • Colette, Gigi (1944) — a teenage girl groomed as a courtesan becomes the adult hero’s love interest; tone is light/comic despite the premise. (Encyclopedia Britannica)
  • Dorothy Strachey (as “Olivia”), Olivia (1949) — classic boarding-school novel about a 16-year-old student’s passion for (and the reciprocation of) her teacher. (Wikipedia, Stanford News)
  • Yasunari Kawabata, The House of the Sleeping Beauties (1961) — elderly men pay to sleep beside drugged “young virgins” (critical work places them roughly mid-teens to early 20s). (Wikipedia, Nichibun Repository)
  • Gabriel García Márquez, One Hundred Years of Solitude (1967) — Aureliano falls for Remedios Moscote when she is nine; he’s made to wait until she menstruates to marry. (LitCharts, CliffsNotes)
  • Thomas Pynchon, Gravity’s Rainbow (1973) — sexualized depiction of Bianca, whom the text describes as “11 or 12,” has generated extensive debate. (gravitys-rainbow.pynchonwiki.com, pynchonnotes.openlibhums.org)
  • Marguerite Duras, The Lover (1984) — an acclaimed autofictional novel about a 15-year-old girl’s affair with a much older man. (Encyclopedia Britannica)
  • Mario Vargas Llosa, In Praise of the Stepmother (1988) — erotic novel in which a stepmother is drawn into a sexual relationship with her pre-teen/early-teen stepson. (Wikipedia, The New Yorker)
  • Haruki Murakami, Kafka on the Shore (2002) — features a 15-year-old protagonist in sexual encounters with an older woman; reviews and summaries note the controversy. (The New Yorker, Encyclopedia.com)
  • André Aciman, Call Me by Your Name (2007) — a 17-year-old and a 24-year-old; celebrated novel/film, frequently discussed in age-of-consent debates. (Encyclopedia Britannica)

If you’d like, I can also split these into “widely read in the Western canon” vs. “non-Western but often cited in the same debates,” or add quick pointers to major critiques for each title.