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  "slug": "multicategory-group-homophily",
  "title": "Multicategory group homophily: constructive feasibility and sharp limits",
  "shortTitle": "With three or more categories every category can look homophilous in groups at once; an exact ceiling says how far, and which budget blocks it",
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  "oneLine": "With three or more categories the two-category impossibility for simultaneous group homophily disappears; an exact test and a closed-form ceiling with a named binding budget say what is possible, and a school example shows the same 4,600 groups passing for 10/10 classrooms but 0/5 school years.",
  "abstract": "Group homophily measures compare how often a category's members find themselves in groups with one, two or more others of their own category against a baseline. Veldt, Benson and Kleinberg (2023) proved that with two categories natural forms of simultaneous group homophily are combinatorially impossible, and asked how these limits change with more categories. This candidate answers the question for a single group size. First, with three or more categories and any full-support baseline whose category participation matches the observed participation, arbitrarily small changes that keep every category's (and every individual's) participation fixed make every category's affinity ratios strictly increase with its number of members; connected, simple, regular finite hypergraphs realise this at every rational composition (Theorem 1, Propositions 2–3). This proves an earlier informal remark of Sarker, Northrup and Jadbabaie. Second, an exact finite list of inequalities describes which strict-majority probabilities can coexist at fixed participation (Theorem 2). Third, a closed-form, attained ceiling bounds how far all majority affinity ratios can rise together, as the minimum of a group-count budget and each category's own and complementary participation budgets (Theorem 3, Corollary 1). Consequences: a short certificate for the two-category odd-size impossibility (Corollary 2) and the fact that at matched participation the baseline must allow groups without a strict majority (Corollary 3). In an exploratory reanalysis of 4,600 distinct primary-school proximity triples, between 8 and 10 of 10 pupil classrooms meet strict-majority homophily across four specifications, against 0 or 1 of 5 merged school years; the years fail only at the two-of-three count because merging roughly doubles its chance rate, and a binary pupil/teacher coding gives a ceiling of 0.641. These results concern measurement feasibility; they do not identify preferences or causal mechanisms. AI-assisted, unrefereed candidate; no external peer review, independent reproduction or formal verification is claimed.",
  "datePublished": "2026-11-03",
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  "keywords": [
    "group homophily",
    "higher-order homophily",
    "hypergraphs",
    "affinity ratio",
    "impossibility theorem",
    "network flows",
    "social networks",
    "school contact data"
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    "Theorem 1 (proof): for q ≥ 3 categories and any full-support baseline with matched participation, arbitrarily small participation-preserving (even individual-participation-preserving) perturbations make every category's affinity ratios strictly increase in its count; Proposition 3 realises this in connected, simple, regular finite hypergraphs at every rational composition.",
    "Theorem 2 (proof): an exact finite list of inequalities decides which strict-majority probabilities can coexist at fixed participation, without enumerating all compositions.",
    "Theorem 3 and Corollary 1 (proof): the largest common multiplier of all majority affinity ratios is λ_max = min{1/A₀, min_c d_c/T_c⁰, min_c (k − d_c)/(T⁰ − T_c⁰ + S_c⁰)}, attained; simultaneous strict-majority homophily is possible iff λ_max > 1. For q equal categories in a three-person multinomial baseline, λ_max = q²/(3q − 2).",
    "Corollaries 2 and 3 (proof): with two categories and odd group size, λ_max ≤ 1 for every activity profile (a short certificate for Veldt et al.'s Theorem 5); at matched participation λ_max ≤ 1/A₀, so the baseline must allow groups without a strict majority.",
    "Section 7 (exploratory, descriptive): in 4,600 school proximity triples, 10/10 classrooms but 0/5 merged school years meet strict-majority homophily under the primary specification (8–10/10 vs 0–1/5 across four); ceilings 3.92 (classrooms), 2.07 (years), 0.641 for pupils versus teachers."
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  "relatedWorks": [
    {
      "citation": "Veldt, Benson and Kleinberg (2023). Combinatorial characterizations and impossibilities for higher-order homophily. Science Advances. Proved the two-category impossibilities and asked how they change with more categories; Proposition 1 and the odd-size result recovered in Corollary 2 are theirs.",
      "url": "https://doi.org/10.1126/sciadv.abq3200",
      "doi": "10.1126/sciadv.abq3200"
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    {
      "citation": "Sarker, Northrup and Jadbabaie (2024). Higher-order homophily on simplicial complexes. Proceedings of the National Academy of Sciences. Studies the same school data and shows group-level class affinities can largely be inherited from pairwise contacts; their earlier preprint remarked informally that three or more labels help.",
      "url": "https://doi.org/10.1073/pnas.2315931121",
      "doi": "10.1073/pnas.2315931121"
    },
    {
      "citation": "Rizi, Michielan, Stegehuis and Kivelä (2025). Homophily within and across groups. Nature Communications. Multicategory and category-coarsening extensions of a maximum-entropy model; does not characterise all count-specific ratios jointly.",
      "url": "https://doi.org/10.1038/s41467-025-66415-2",
      "doi": "10.1038/s41467-025-66415-2"
    },
    {
      "citation": "Kumano, Nishimura and Kimura (2026). Higher-order homophily analysis for hypergraphs with time-varying node categories. Applied Network Science. Temporal category and category-pair measures.",
      "url": "https://doi.org/10.1007/s41109-026-00801-7",
      "doi": "10.1007/s41109-026-00801-7"
    },
    {
      "citation": "Wang, Zhou, Li, Zhao and Qi (2026). Measuring the higher-order homophily in a general social hypergraph. Chaos. Extends measurement to groups of different sizes.",
      "url": "https://doi.org/10.1063/5.0345566",
      "doi": "10.1063/5.0345566"
    },
    {
      "citation": "Chun, Yoon, Choe, Lee and Shin (2026). From binary to general attributes: attributed hypergraph generation with realistic interplay between structure and attributes. Knowledge and Information Systems. Generative models with categorical affinity profiles.",
      "url": "https://doi.org/10.1007/s10115-026-02850-x",
      "doi": "10.1007/s10115-026-02850-x"
    },
    {
      "citation": "McPherson, Smith-Lovin and Cook (2001). Birds of a Feather: Homophily in Social Networks. Annual Review of Sociology. The standard account of homophily.",
      "url": "https://doi.org/10.1146/annurev.soc.27.1.415",
      "doi": "10.1146/annurev.soc.27.1.415"
    },
    {
      "citation": "Feld (1981). The Focused Organization of Social Ties. American Journal of Sociology. Shared settings create opportunities for contact, so homophily reflects opportunity as well as preference.",
      "url": "https://doi.org/10.1086/227352",
      "doi": "10.1086/227352"
    },
    {
      "citation": "Gale (1957). A theorem on flows in networks. Pacific Journal of Mathematics. The supply-demand feasibility theorem behind Theorems 2 and 3.",
      "url": "https://doi.org/10.2140/pjm.1957.7.1073",
      "doi": "10.2140/pjm.1957.7.1073"
    },
    {
      "citation": "Ford and Fulkerson (1956). Maximal Flow Through a Network. Canadian Journal of Mathematics. Maximum-flow/minimum-cut duality used in the proofs.",
      "url": "https://doi.org/10.4153/CJM-1956-045-5",
      "doi": "10.4153/CJM-1956-045-5"
    },
    {
      "citation": "Wang and Wang (2016). Joint Mixability. Mathematics of Operations Research. Constant-sum couplings related to the composition geometry.",
      "url": "https://doi.org/10.1287/moor.2015.0755",
      "doi": "10.1287/moor.2015.0755"
    },
    {
      "citation": "Stehlé et al. (2011). High-Resolution Measurements of Face-to-Face Contact Patterns in a Primary School. PLoS ONE. The original sensor study of the school data used in Section 7.",
      "url": "https://doi.org/10.1371/journal.pone.0023176",
      "doi": "10.1371/journal.pone.0023176"
    },
    {
      "citation": "Gemmetto, Barrat and Cattuto (2014). Mitigation of infectious disease at school: targeted class closure vs school closure. BMC Infectious Diseases. Documents the classroom and school-year structure of the same data.",
      "url": "https://doi.org/10.1186/s12879-014-0695-9",
      "doi": "10.1186/s12879-014-0695-9"
    },
    {
      "citation": "Benson, Abebe, Schaub, Jadbabaie and Kleinberg (2018). Simplicial closure and higher-order link prediction. Proceedings of the National Academy of Sciences. Source of the temporal group (clique) release.",
      "url": "https://doi.org/10.1073/pnas.1800683115",
      "doi": "10.1073/pnas.1800683115"
    },
    {
      "citation": "Chodrow, Veldt and Benson (2021). Generative hypergraph clustering: From blockmodels to modularity. Science Advances. Source of the labelled hypergraph release analysed in Section 7.",
      "url": "https://doi.org/10.1126/sciadv.abh1303",
      "doi": "10.1126/sciadv.abh1303"
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