{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "f2b5b39d",
   "metadata": {},
   "source": [
    "# 18 — Ce qu'il faut demander au titre de l'article 40\n",
    "\n",
    "Le [notebook 17](17_rang_servi.ipynb) s'est terminé sur un constat : aucun jeu public ne porte à\n",
    "la fois le **rang servi** et une **étiquette de point de vue interprétable**. Il reste une voie,\n",
    "prévue par l'article 40 du *Digital Services Act* et rendue opérationnelle par le règlement\n",
    "délégué (UE) 2025/2050, entré en vigueur le 29 octobre 2025 : **demander la donnée**.\n",
    "\n",
    "Une demande n'est recevable que si elle est **nécessaire et proportionnée** — article 40(8)(e)\n",
    "du DSA, article 8(d) du règlement délégué. « Donnez-nous vos journaux » n'est ni l'un ni\n",
    "l'autre : cela réclame des données personnelles dont l'analyse n'a aucun besoin, et cela offre à\n",
    "la plateforme le motif de refus le plus facile, la sécurité du service et le secret des affaires\n",
    "(article 40(5)).\n",
    "\n",
    "Ce notebook fait le travail inverse. Il définit les **quatre tableaux agrégés** dont les mesures\n",
    "de ce dépôt ont réellement besoin, et vérifie qu'elles s'y retrouvent **à l'identique**. La\n",
    "demande cesse alors d'être un accès à négocier pour devenir un livrable spécifié.\n",
    "\n",
    "**Ce que ce notebook établit :**\n",
    "\n",
    "* les quatre mesures qui décident de tout — test d'échangeabilité, sévérité $\\eta$, diversité\n",
    "  aveugle au rang, diversité consciente du rang — se recalculent **exactement** depuis des\n",
    "  tableaux qui ne contiennent **aucune ligne par lecteur** ;\n",
    "* ce qui est demandé pèse **quelques milliers de lignes** là où le journal brut en compte des\n",
    "  millions : sur Baidu-ULTR, 5 543 lignes pour 524 164 documents servis, soit un rapport de 95 ;\n",
    "* le **seuil de confidentialité n'est pas neutre** — supprimer les cellules de moins de 20\n",
    "  impressions déplace la sévérité estimée de 1,10 à 1,40, soit 27 % ;\n",
    "* et le tableau 4 suffit à constater l'**enterrement**, la grandeur de contrôle que le\n",
    "  [mémorandum](../docs/memorandum.md) demande d'imposer.\n",
    "\n",
    "La demande elle-même, rédigée et prête à déposer, est à\n",
    "[l'article 40](../docs/article-40.md)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "0cf7d5d4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-23T13:41:05.950270Z",
     "iopub.status.busy": "2026-08-23T13:41:05.950014Z",
     "iopub.status.idle": "2026-08-23T13:41:06.673261Z",
     "shell.execute_reply": "2026-08-23T13:41:06.672846Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Baidu-ULTR : 64200 sessions, 524164 documents servis\n",
      "MIND       : 156965 fils, 5843444 contenus servis\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from ide.aggregates import (\n",
    "    aggregate,\n",
    "    blind_distribution,\n",
    "    exchangeability_from,\n",
    "    served_distribution,\n",
    "    severity_from,\n",
    "    suppression_sensitivity,\n",
    ")\n",
    "from ide.exposure import SOURCES, load_digest as load_exposure_digest\n",
    "from ide.gaming import canonical_positions, position_entropy\n",
    "from ide.logs import Impressions, exchangeability_test\n",
    "from ide.mind import load_digest as load_mind_digest\n",
    "from ide.offpolicy import estimate_position_bias\n",
    "from ide.plotting import PALETTE, save_figure, use_project_style\n",
    "from ide.radio import rank_weights\n",
    "from ide.ranking import optimal_ranking_under\n",
    "\n",
    "use_project_style()\n",
    "\n",
    "exposure = load_exposure_digest()\n",
    "baidu = exposure.impressions(\"baidu\")\n",
    "mind = load_mind_digest().impressions(\"train\")\n",
    "\n",
    "print(f\"Baidu-ULTR : {baidu.feed_count} sessions, {baidu.served} documents servis\")\n",
    "print(f\"MIND       : {mind.feed_count} fils, {mind.served} contenus servis\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0eefcef1",
   "metadata": {},
   "source": [
    "## 1. Les quatre tableaux\n",
    "\n",
    "| | Tableau | Clé | Valeur |\n",
    "|---|---|---|---|\n",
    "| 1 | profils de fils | (profil de rangs, nombre de clics du fil) | nombre de fils |\n",
    "| 2 | clics par rang | (profil de rangs, nombre de clics du fil, rang) | nombre de clics |\n",
    "| 3 | cellules | (contenu, rang) *et propension si connue* | impressions, clics |\n",
    "| 4 | exposition | (rang, point de vue déclaré) | impressions |\n",
    "\n",
    "Le **profil de rangs** est la liste des rangs qu'un fil occupe. L'indexer par la seule longueur\n",
    "serait plus court et **faux** dès qu'une page saute des rangs — c'est la correction qu'a imposée\n",
    "Baidu-ULTR. Le **nombre de clics du fil**, second index des tableaux 1 et 2, n'est pas un\n",
    "ornement non plus : sans lui, les fils dont *tout* a été cliqué ne peuvent pas être écartés, et\n",
    "le test se décale.\n",
    "\n",
    "Aucune ligne ne désigne un lecteur. Un fil n'y figure que par sa forme et par le nombre de clics\n",
    "qu'il a reçus."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c34a061e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-23T13:41:06.674122Z",
     "iopub.status.busy": "2026-08-23T13:41:06.673995Z",
     "iopub.status.idle": "2026-08-23T13:41:10.654715Z",
     "shell.execute_reply": "2026-08-23T13:41:10.654203Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "journal       lignes servies   lignes demandées   rapport   profils\n",
      "--------------------------------------------------------------------\n",
      "Baidu-ULTR            524164               5543      94.6      1007\n",
      "MIND                 5843444              57906     100.9       296\n"
     ]
    }
   ],
   "source": [
    "# Le condensé versionné ne retient pas l'identité des contenus ligne à ligne ; les tableaux 1\n",
    "# et 2 n'en dépendent pas, et c'est d'eux seuls que vient le test d'échangeabilité.\n",
    "def with_placeholder(impressions):\n",
    "    return Impressions(items=impressions.ranks, ranks=impressions.ranks,\n",
    "                       clicks=impressions.clicks, feeds=impressions.feeds,\n",
    "                       feed_lengths=impressions.feed_lengths)\n",
    "\n",
    "\n",
    "requests = {name: aggregate(with_placeholder(impressions))\n",
    "            for name, impressions in ((\"Baidu-ULTR\", baidu), (\"MIND\", mind))}\n",
    "\n",
    "raw_bytes = {\"Baidu-ULTR\": SOURCES[\"baidu\"][1],\n",
    "             \"MIND\": 92_019_716 + 42_838_544}\n",
    "\n",
    "print(f\"{'journal':12s} {'lignes servies':>15s} {'lignes demandées':>18s} {'rapport':>9s}\"\n",
    "      f\" {'profils':>9s}\")\n",
    "print(\"-\" * 68)\n",
    "for name, request in requests.items():\n",
    "    served = baidu.served if name == \"Baidu-ULTR\" else mind.served\n",
    "    profiles = request.profile_offsets.size - 1\n",
    "    print(f\"{name:12s} {served:15d} {request.rows:18d} {served / request.rows:9.1f}\"\n",
    "          f\" {profiles:9d}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "76b0e808",
   "metadata": {},
   "source": [
    "## 2. La preuve que cela suffit\n",
    "\n",
    "Quatre mesures, calculées deux fois : directement sur le journal, puis sur les seuls tableaux\n",
    "agrégés. L'écart doit être **nul**, pas petit."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "ef49a271",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-23T13:41:10.655566Z",
     "iopub.status.busy": "2026-08-23T13:41:10.655495Z",
     "iopub.status.idle": "2026-08-23T13:41:10.789720Z",
     "shell.execute_reply": "2026-08-23T13:41:10.789214Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test d'échangeabilité — le contrôle qui décide si un journal est corrigible\n",
      "\n",
      "journal              direct   depuis les tableaux        écart\n",
      "--------------------------------------------------------------\n",
      "Baidu-ULTR      -205.719247           -205.719247     2.84e-13\n",
      "MIND               0.115856              0.115856     3.29e-12\n"
     ]
    }
   ],
   "source": [
    "print(\"Test d'échangeabilité — le contrôle qui décide si un journal est corrigible\\n\")\n",
    "print(f\"{'journal':12s} {'direct':>14s} {'depuis les tableaux':>21s} {'écart':>12s}\")\n",
    "print(\"-\" * 62)\n",
    "checks = {}\n",
    "for name, impressions in ((\"Baidu-ULTR\", baidu), (\"MIND\", mind)):\n",
    "    direct = exchangeability_test(impressions)\n",
    "    from_tables = exchangeability_from(requests[name])\n",
    "    checks[name] = (direct.deviation, from_tables.deviation)\n",
    "    print(f\"{name:12s} {direct.deviation:14.6f} {from_tables.deviation:21.6f}\"\n",
    "          f\" {abs(direct.deviation - from_tables.deviation):12.2e}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "9069a820",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-23T13:41:10.790465Z",
     "iopub.status.busy": "2026-08-23T13:41:10.790395Z",
     "iopub.status.idle": "2026-08-23T13:41:10.893567Z",
     "shell.execute_reply": "2026-08-23T13:41:10.893184Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sévérité du biais de position, sur Baidu-ULTR\n",
      "\n",
      "  directe            : 1.098729 ± 0.088996\n",
      "  depuis le tableau 3: 1.098729 ± 0.088996\n",
      "  écart              : 0.00e+00\n",
      "  lignes du tableau 3: 1292\n"
     ]
    }
   ],
   "source": [
    "items, ranks, clicks = exposure.rows(\"baidu\")\n",
    "cells = Impressions(items=items, ranks=ranks, clicks=clicks,\n",
    "                    feeds=np.arange(items.size), feed_lengths=np.ones(items.size, dtype=np.int64))\n",
    "cell_request = aggregate(cells)\n",
    "\n",
    "direct_severity = estimate_position_bias(items, ranks, clicks, minimum_impressions=5)\n",
    "table_severity = severity_from(cell_request, minimum_impressions=5)\n",
    "\n",
    "print(\"Sévérité du biais de position, sur Baidu-ULTR\\n\")\n",
    "print(f\"  directe            : {direct_severity.severity:.6f} ± \"\n",
    "      f\"{direct_severity.standard_error:.6f}\")\n",
    "print(f\"  depuis le tableau 3: {table_severity.severity:.6f} ± \"\n",
    "      f\"{table_severity.standard_error:.6f}\")\n",
    "print(f\"  écart              : {abs(direct_severity.severity - table_severity.severity):.2e}\")\n",
    "print(f\"  lignes du tableau 3: {cell_request.cell_items.size}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ef7ad2f5",
   "metadata": {},
   "source": [
    "## 3. Ce que le tableau 4 permet de constater : l'enterrement\n",
    "\n",
    "Le [mémorandum](../docs/memorandum.md) demande d'imposer une mesure de diversité **consciente du\n",
    "rang**, et de contrôler l'écart avec la mesure aveugle — l'écart d'**enterrement**, qui vaut zéro\n",
    "pour une plateforme qui ne relègue pas.\n",
    "\n",
    "Cet écart se calcule sur le seul tableau 4. Voici **trois fils de composition identique** :\n",
    "celui que le [rang adverse](../docs/rang-adverse.md) a montré optimal sous un plancher aveugle,\n",
    "le même entrelacé, et le même retourné."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "e024483e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-23T13:41:10.894371Z",
     "iopub.status.busy": "2026-08-23T13:41:10.894302Z",
     "iopub.status.idle": "2026-08-23T13:41:11.733203Z",
     "shell.execute_reply": "2026-08-23T13:41:11.732610Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "fil conforme au plancher aveugle   : 00000123\n",
      "fil entrelacé                      : 01020300\n",
      "fil retourné                       : 32100000\n",
      "\n",
      "enterré      composition [0.625 0.125 0.125 0.125]  exposée [0.84  0.061 0.053 0.046]\n",
      "             écart composition/exposition 0.215   part d'attention aux points de vue minoritaires 0.160\n",
      "entrelacé    composition [0.625 0.125 0.125 0.125]  exposée [0.663 0.184 0.092 0.061]\n",
      "             écart composition/exposition 0.097   part d'attention aux points de vue minoritaires 0.337\n",
      "retourné     composition [0.625 0.125 0.125 0.125]  exposée [0.325 0.123 0.184 0.368]\n",
      "             écart composition/exposition 0.302   part d'attention aux points de vue minoritaires 0.675\n"
     ]
    }
   ],
   "source": [
    "VIEWPOINTS, SLOTS = 4, 8\n",
    "CATALOGUE = canonical_positions(VIEWPOINTS)\n",
    "RELEVANCE = np.array([0.90, 0.45, 0.25, 0.15])\n",
    "\n",
    "burying = optimal_ranking_under(\n",
    "    lambda weights: position_entropy(weights, CATALOGUE, CATALOGUE),\n",
    "    RELEVANCE, SLOTS, 0.70, rank_aware=False,\n",
    ")\n",
    "buried_feed = burying.assignment\n",
    "reversed_feed = buried_feed[::-1]\n",
    "# Entrelacement : la même composition, répartie le plus régulièrement possible sur les rangs.\n",
    "minority = [value for value in buried_feed if value != 0]\n",
    "interleaved = []\n",
    "remaining = list(minority)\n",
    "for slot in range(SLOTS):\n",
    "    if remaining and slot % 2 == 1:\n",
    "        interleaved.append(remaining.pop(0))\n",
    "    else:\n",
    "        interleaved.append(0)\n",
    "interleaved = np.asarray(interleaved + remaining, dtype=int)[:SLOTS]\n",
    "\n",
    "for label, feed in ((\"conforme au plancher aveugle\", buried_feed),\n",
    "                    (\"entrelacé\", interleaved),\n",
    "                    (\"retourné\", reversed_feed)):\n",
    "    print(f\"fil {label:30s} : {''.join(str(v) for v in feed)}\")\n",
    "print()\n",
    "\n",
    "REPEATS = 500\n",
    "comparison = {}\n",
    "for label, assignment in ((\"enterré\", buried_feed), (\"entrelacé\", interleaved),\n",
    "                          (\"retourné\", reversed_feed)):\n",
    "    categories = np.tile(assignment, REPEATS)\n",
    "    impressions = Impressions(\n",
    "        items=categories.astype(np.int64),\n",
    "        ranks=np.tile(np.arange(1, SLOTS + 1), REPEATS).astype(np.int64),\n",
    "        clicks=np.zeros(categories.size),\n",
    "        feeds=np.repeat(np.arange(REPEATS), SLOTS).astype(np.int64),\n",
    "        feed_lengths=np.full(REPEATS, SLOTS, dtype=np.int64),\n",
    "    )\n",
    "    request = aggregate(impressions, categories=categories)\n",
    "    blind = blind_distribution(request)\n",
    "    served = served_distribution(request)\n",
    "    comparison[label] = (blind, served)\n",
    "    minority_share = 1.0 - served[0]\n",
    "    print(f\"{label:12s} composition {np.round(blind, 3)}  exposée {np.round(served, 3)}\")\n",
    "    print(f\"{'':12s} écart composition/exposition {0.5 * np.abs(blind - served).sum():.3f}\"\n",
    "          f\"   part d'attention aux points de vue minoritaires {minority_share:.3f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e3431b23",
   "metadata": {},
   "source": [
    "Les trois fils ont **la même composition** — même nombre de contenus de chaque point de vue — et\n",
    "trois expositions différentes. Un régulateur qui ne reçoit que le tableau 4 le voit ; un\n",
    "régulateur qui ne reçoit que la composition ne le voit pas.\n",
    "\n",
    "L'écart entre composition et exposition **ne vaut pas zéro pour un fil neutre** : avec une remise\n",
    "en $1/R$, seule une répartition parfaitement uniforme des points de vue sur les rangs\n",
    "l'annulerait. Ce qu'il sépare, ce sont des **ordres**, à composition constante — et la grandeur\n",
    "directement lisible est la part d'attention laissée aux points de vue minoritaires : 0,375 de la\n",
    "composition, contre ce que chaque ordre en expose réellement.\n",
    "\n",
    "## 4. Ce que le seuil de confidentialité coûte\n",
    "\n",
    "Supprimer les lignes de faible effectif protège les lecteurs. Ce n'est pas gratuit : les\n",
    "cellules rares sont aussi celles des rangs profonds, dont l'estimation de $\\eta$ tire\n",
    "l'essentiel de son information."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "6e5fd68f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-23T13:41:11.733984Z",
     "iopub.status.busy": "2026-08-23T13:41:11.733911Z",
     "iopub.status.idle": "2026-08-23T13:41:12.137807Z",
     "shell.execute_reply": "2026-08-23T13:41:12.137162Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " seuil   sévérité  erreur type   lignes demandées\n",
      "--------------------------------------------------\n",
      "     0      1.099        0.089               1333\n",
      "     5      1.099        0.089               1331\n",
      "    20      1.395        0.114                265\n",
      "    50      1.437        0.152                150\n",
      "   100      1.374        0.215                 98\n",
      "\n",
      "De 5 à 20 impressions, la sévérité passe de 1.10 à 1.40, soit +27 %.\n",
      "Le seuil doit donc être négocié et publié avec le résultat, pas laissé au hasard.\n"
     ]
    }
   ],
   "source": [
    "sensitivity = suppression_sensitivity(cells, thresholds=(0, 5, 20, 50, 100))\n",
    "\n",
    "print(f\"{'seuil':>6s} {'sévérité':>10s} {'erreur type':>12s} {'lignes demandées':>18s}\")\n",
    "print(\"-\" * 50)\n",
    "for threshold, (severity, error, rows) in sensitivity.items():\n",
    "    print(f\"{threshold:6d} {severity:10.3f} {error:12.3f} {rows:18d}\")\n",
    "\n",
    "reference = sensitivity[5][0]\n",
    "print(f\"\\nDe 5 à 20 impressions, la sévérité passe de {sensitivity[5][0]:.2f} à \"\n",
    "      f\"{sensitivity[20][0]:.2f}, soit {100 * (sensitivity[20][0] / reference - 1):+.0f} %.\")\n",
    "print(\"Le seuil doit donc être négocié et publié avec le résultat, pas laissé au hasard.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f0e055e4",
   "metadata": {},
   "source": [
    "## 5. La figure"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "ecf668f8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-23T13:41:12.138862Z",
     "iopub.status.busy": "2026-08-23T13:41:12.138767Z",
     "iopub.status.idle": "2026-08-23T13:41:12.692922Z",
     "shell.execute_reply": "2026-08-23T13:41:12.692335Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1488x1008 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "figure, axes = plt.subplots(2, 2, figsize=(12.4, 8.4))\n",
    "\n",
    "# (a) ce que la demande pèse\n",
    "ax = axes[0, 0]\n",
    "names = list(requests)\n",
    "served_rows = [baidu.served, mind.served]\n",
    "asked_rows = [requests[name].rows for name in names]\n",
    "positions = np.arange(len(names))\n",
    "ax.bar(positions - 0.18, served_rows, width=0.34, color=PALETTE[\"disorder\"], alpha=0.85,\n",
    "       label=\"lignes du journal brut\")\n",
    "ax.bar(positions + 0.18, asked_rows, width=0.34, color=PALETTE[\"remedy\"], alpha=0.85,\n",
    "       label=\"lignes demandées\")\n",
    "for index, (served, asked) in enumerate(zip(served_rows, asked_rows, strict=True)):\n",
    "    ax.text(index + 0.18, asked * 1.4, f\"÷ {served / asked:.0f}\", ha=\"center\", fontsize=9,\n",
    "            color=PALETTE[\"remedy\"])\n",
    "ax.set_yscale(\"log\")\n",
    "ax.set_xticks(positions)\n",
    "ax.set_xticklabels(names)\n",
    "ax.set_ylabel(\"lignes (échelle log)\")\n",
    "ax.set_title(\"(a) ce que la demande pèse, face au journal\")\n",
    "ax.legend(loc=\"upper right\", fontsize=8)\n",
    "\n",
    "# (b) l'exactitude\n",
    "ax = axes[0, 1]\n",
    "labels = [\"échangeabilité\\nBaidu-ULTR\", \"échangeabilité\\nMIND\", \"sévérité $\\\\eta$\\nBaidu-ULTR\"]\n",
    "gaps = [abs(checks[\"Baidu-ULTR\"][0] - checks[\"Baidu-ULTR\"][1]),\n",
    "        abs(checks[\"MIND\"][0] - checks[\"MIND\"][1]),\n",
    "        abs(direct_severity.severity - table_severity.severity)]\n",
    "floor = 1e-18\n",
    "ax.bar(labels, [max(gap, floor) for gap in gaps], color=PALETTE[\"order\"], alpha=0.85, width=0.5)\n",
    "ax.axhline(1e-12, color=PALETTE[\"neutral\"], linestyle=\":\", linewidth=1.2)\n",
    "ax.text(2.45, 2e-12, \"erreur d'arrondi ($10^{-12}$)\", fontsize=8, color=PALETTE[\"neutral\"],\n",
    "        ha=\"right\")\n",
    "if gaps[2] == 0.0:\n",
    "    ax.text(2, floor * 3, \"exactement 0\", fontsize=8, color=PALETTE[\"order\"], ha=\"center\")\n",
    "ax.set_yscale(\"log\")\n",
    "ax.set_ylim(floor / 2, 1e-6)\n",
    "ax.set_ylabel(\"écart entre mesure directe et mesure agrégée\")\n",
    "ax.set_title(\"(b) les deux mesures coïncident\")\n",
    "ax.tick_params(axis=\"x\", labelsize=8)\n",
    "\n",
    "# (c) le seuil de confidentialité\n",
    "ax = axes[1, 0]\n",
    "thresholds = np.array(list(sensitivity))\n",
    "severities = np.array([sensitivity[t][0] for t in thresholds])\n",
    "errors = np.array([sensitivity[t][1] for t in thresholds])\n",
    "ax.errorbar(np.arange(thresholds.size), severities, yerr=1.96 * errors, fmt=\"o-\",\n",
    "            color=PALETTE[\"field\"], markersize=5, capsize=4, label=\"sévérité estimée\")\n",
    "ax.axhline(severities[0], color=PALETTE[\"neutral\"], linestyle=\":\", linewidth=1.2)\n",
    "ax.text(0.05, severities[0] - 0.06, \"sans suppression\", fontsize=8, color=PALETTE[\"neutral\"])\n",
    "ax.set_xticks(np.arange(thresholds.size))\n",
    "ax.set_xticklabels([str(t) for t in thresholds])\n",
    "ax.set_xlabel(\"seuil de suppression (impressions par cellule)\")\n",
    "ax.set_ylabel(\"sévérité $\\\\hat\\\\eta$\")\n",
    "ax.set_title(\"(c) le seuil de confidentialité déplace le résultat\")\n",
    "\n",
    "twin = ax.twinx()\n",
    "twin.plot(np.arange(thresholds.size), [sensitivity[t][2] for t in thresholds], \"s--\",\n",
    "          color=PALETTE[\"neutral\"], markersize=4, alpha=0.7)\n",
    "twin.set_ylabel(\"lignes demandées\", color=PALETTE[\"neutral\"], fontsize=9)\n",
    "twin.set_yscale(\"log\")\n",
    "twin.grid(False)\n",
    "\n",
    "# (d) l'enterrement, vu depuis le seul tableau 4\n",
    "ax = axes[1, 1]\n",
    "width = 0.2\n",
    "viewpoints = np.arange(VIEWPOINTS)\n",
    "blind_buried, served_buried = comparison[\"enterré\"]\n",
    "_, served_honest = comparison[\"entrelacé\"]\n",
    "ax.bar(viewpoints - width, blind_buried, width=width, color=PALETTE[\"neutral\"], alpha=0.85,\n",
    "       label=\"composition (identique aux trois fils)\")\n",
    "ax.bar(viewpoints, served_buried, width=width, color=PALETTE[\"disorder\"], alpha=0.85,\n",
    "       label=\"exposition — fil enterré\")\n",
    "ax.bar(viewpoints + width, served_honest, width=width, color=PALETTE[\"remedy\"], alpha=0.85,\n",
    "       label=\"exposition — fil entrelacé\")\n",
    "ax.set_xticks(viewpoints)\n",
    "ax.set_xticklabels([f\"point de vue {v}\" for v in viewpoints], fontsize=8)\n",
    "ax.set_ylabel(\"part de l'attention\")\n",
    "ax.set_title(\"(d) l'enterrement, constaté sur le seul tableau 4\")\n",
    "ax.legend(loc=\"upper right\", fontsize=8)\n",
    "\n",
    "save_figure(figure, \"fig18_demande_article_40\")\n",
    "plt.show()"
   ]
  },
  {
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   "id": "30d0e7cf",
   "metadata": {},
   "source": [
    "## 6. Ce que cette spécification change à la demande\n",
    "\n",
    "**Elle retire à la plateforme son motif de refus le plus facile.** L'article 40(5) permet de\n",
    "demander l'amendement d'une requête au motif que la divulgation créerait des vulnérabilités de\n",
    "sécurité ou révélerait des secrets d'affaires. Des comptages par rang et par point de vue\n",
    "déclaré ne révèlent ni le classement, ni ses paramètres, ni les contenus : ils disent **ce qui a\n",
    "été exposé**, pas comment la plateforme a décidé de l'exposer.\n",
    "\n",
    "**Elle rend la proportionnalité vérifiable.** Ce qui est demandé se chiffre : quelques milliers\n",
    "de lignes, un rapport de 95 sur Baidu-ULTR, et aucune ligne par lecteur.\n",
    "\n",
    "**Elle déplace la charge de la preuve.** Une demande spécifiée peut être refusée, mais le refus\n",
    "doit alors porter sur autre chose que sa forme — et c'est très précisément ce qu'un régulateur\n",
    "peut arbitrer.\n",
    "\n",
    "**Ce qu'elle ne change pas.** L'article 40(8)(a) exige du demandeur qu'il soit affilié à un\n",
    "organisme de recherche : ce dépôt, tenu par une personne seule, n'y est **pas éligible** en\n",
    "l'état. La demande rédigée à [l'article 40](../docs/article-40.md) est donc un **modèle**, à\n",
    "déposer par un organisme qui en remplit les conditions — et la voie de l'article 40(12), ouverte\n",
    "aux associations sans but lucratif, ne donne accès qu'aux données **publiquement accessibles**,\n",
    "c'est-à-dire à tout sauf ce qui est demandé ici."
   ]
  }
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