d4-journals-mss-2021-0007

· ? (d4-journals-mss-2021-0007)

no mirror
paperd4-journals-mss-2021-0007
authors—
venue?
filed underunclassified
judged bygpt-6-luna / xhigh (triple__luna__xhigh__c6r1)
judge confidencehigh
authors would recognise itno

Why no mirror

Theorem 3.7 and the paper’s other named results concern representation size and structure, not a computational problem. The proposed two-bloc mass model changes what representation dimension means and supplies no computational task anchored to a result in the paper.

fails bit a — no named computational result to mirror

What the mirror covers

No result has a continuous computational mirror; the dimension and Boolean-dimension bounds and constructions remain unmirrored.

The case FOR (proponent)

This paper contains no named computational-complexity result of the required kind, so I can’t give an honest anchored case for a continuous computational mirror.

The closest result is Theorem 3.7, proved in this paper: for every \(n\ge4\) divisible by \(4\), there exists a complete simple game on \(n\) voters with exactly two voter types whose dimension is at least
\[ A(n/2,4;n/4)\ge {n/2\choose n/4}\frac{2}{n}\ge \frac{4\cdot 2^{n/2}}{n^2}. \]
That is an exponential lower bound on the representation dimension of certain games. It does not establish a complexity classification for a computational problem, such as finding the dimension or deciding whether it exceeds a threshold. The other named results likewise give representation bounds or constructions, rather than algorithmic complexity results.

A continuum version of the representation question might be worth posing separately, but it would not be a mirror anchored to a qualifying result in this paper.

The case AGAINST (opponent, writing after the proponent)

The proponent raised no qualifying anchor, so there is no computational result to defeat. Theorem 3.7 is the closest candidate: it proves an exponential lower bound on the dimension of a complete simple game with two voter types. But dimension here is a representation measure—the minimum number of weighted games whose intersection represents the rule—not the worst-case complexity of a computational problem. The paper does not study an algorithm for finding that dimension, deciding whether it exceeds a threshold, or solving an intervention problem. The other results are likewise representation bounds and structural constructions.

The best attempt at a mirror is to take two nonatomic voter blocs and extend the family from Theorem 3.7 to mass vectors \((x,y)\), with winning condition \(x\ge 1/4\) or \(x+y\ge 1/2\). That does make the population continuous. But it changes what dimension measures. A weighted game with one weight per bloc is a halfspace in \((x,y)\); an intersection of such games is convex, while the extended winning region is not. To retain the paper’s intersection-dimension question, one would need to let weighted representations distinguish individuals inside each bloc. That restores the atomized coalition structure and the identity-level choices used by the coding and trading-transform argument. Allowing arbitrary weight functions on a nonatomic population instead creates a new function-space representation problem, with no computational question or encoding supplied by this paper.

There is no valid objection that the paper lacks a plausible high-multiplicity regime: its two-type construction is positive evidence for one. That makes a related continuous geometric study conceivable. The negative case is narrower, but stronger for ChoCo’s stated remit: the paper’s central results do not give a computational problem to continuize, and the most natural mass-level extension changes the representation question rather than mirroring it. I can defend excluding this paper as a target for the programme; I cannot honestly establish the universal claim that no worthwhile continuous question could grow from it.

The adversarial triple: the proponent anchors on up to three named results; the opponent sees that case and must defeat every anchor; the judge decides which case convinced it. These are the pipeline’s own outputs, generated by tools/triple_run.py — no human edited them. The paper’s own text is not reproduced here beyond the quoted statement above.