{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "377c26e1",
   "metadata": {},
   "source": [
    "# 24 — Les deux dernières colonnes, et une hypothèse abandonnée\n",
    "\n",
    "Le [notebook 23](23_exposition_mesuree.ipynb) s'est terminé sur deux colonnes laissées de côté :\n",
    "\n",
    "> `slipoff_count_after_click` et `media_type` n'ont pas été exploitées : la première compte les\n",
    "> documents sortis de l'écran après un clic, ce qui affinerait la mesure ; la seconde distingue\n",
    "> les formats, dont la littérature indique qu'ils modifient l'attention à rang égal.\n",
    "\n",
    "Ce notebook les lit. L'une confirme une hypothèse par une voie indépendante, l'autre en établit\n",
    "une nouvelle — et une troisième, que j'avais formulée avec assurance au chapitre précédent, ne\n",
    "survit pas à sa vérification.\n",
    "\n",
    "**Ce que ce notebook établit :**\n",
    "\n",
    "* `slipoff_count_after_click` est non nul pour **43,7 %** des lignes cliquées et **0,5 %** des\n",
    "  autres. Il **mesure le retour** : après un clic, le lecteur revient et fait défiler. C'est la\n",
    "  réfutation de la cascade par un chemin qui ne doit rien au test précédent ;\n",
    "* un **format enrichi** au-dessus réduit l'examen en dessous de **8,4 points** en médiane, à rang\n",
    "  **et** à hauteur de page comparables. L'effet ne passe donc pas par la géométrie ;\n",
    "* et l'hypothèse du **pli d'écran** — « l'exposition serait fonction des pixels, non du rang » —\n",
    "  est **fausse**. Le rang explique mieux que les pixels ($R^2$ de McFadden $0{,}082$ contre\n",
    "  $0{,}057$), et les pixels n'ajoutent que $0{,}0007$ une fois le rang connu."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "5e48e6d4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-23T13:28:09.705749Z",
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     "shell.execute_reply": "2026-08-23T13:28:10.456045Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "524164 lignes, 64200 sessions\n",
      "formats enrichis : 31.2 % des lignes, 437 valeurs distinctes\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pyarrow.feather as feather\n",
    "\n",
    "from ide.exposure import source_path\n",
    "from ide.plotting import PALETTE, save_figure, use_project_style\n",
    "\n",
    "use_project_style()\n",
    "\n",
    "# Six colonnes sur les vingt-neuf du fichier. Les embeddings, qui font tout son poids, ne sont\n",
    "# pas lus. Le condensé versionné ne porte pas ces mesures : ce notebook est le seul du dépôt à\n",
    "# lire le journal brut, et il le dit.\n",
    "table = feather.read_table(source_path(\"baidu\"), columns=[\n",
    "    \"query_no\", \"position\", \"click\", \"displayed_time\",\n",
    "    \"slipoff_count_after_click\", \"media_type\", \"serp_height\"])\n",
    "\n",
    "sessions = np.asarray(table[\"query_no\"])\n",
    "_, feeds = np.unique(sessions, return_inverse=True)\n",
    "position = np.asarray(table[\"position\"]).astype(int)\n",
    "click = np.asarray(table[\"click\"]).astype(float)\n",
    "examined = (np.asarray(table[\"displayed_time\"]).astype(float) > 0).astype(float)\n",
    "slipoff = np.asarray(table[\"slipoff_count_after_click\"]).astype(float)\n",
    "height = np.asarray(table[\"serp_height\"]).astype(float)\n",
    "rich = (np.asarray(table[\"media_type\"]) != 0).astype(float)\n",
    "\n",
    "order = np.lexsort((position, feeds))\n",
    "\n",
    "\n",
    "def cumulate(values):\n",
    "    # Somme des valeurs situées AU-DESSUS, dans la même session.\n",
    "    total = np.cumsum(values[order])\n",
    "    starts = np.concatenate([[0], np.flatnonzero(np.diff(feeds[order])) + 1])\n",
    "    base = np.zeros(total.size)\n",
    "    base[starts] = total[starts] - values[order][starts]\n",
    "    result = np.empty(total.size)\n",
    "    result[order] = total - values[order] - np.maximum.accumulate(base)\n",
    "    return result\n",
    "\n",
    "\n",
    "pixels_above = cumulate(height)\n",
    "rich_above = cumulate(rich)\n",
    "\n",
    "print(f\"{position.size} lignes, {feeds.max() + 1} sessions\")\n",
    "print(f\"formats enrichis : {100 * rich.mean():.1f} % des lignes, {int(np.unique(np.asarray(table['media_type'])).size)} valeurs distinctes\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "796daea2",
   "metadata": {},
   "source": [
    "## 1. Le retour après clic, mesuré\n",
    "\n",
    "Le notebook précédent avait constaté que l'examen se poursuit sous un clic, et proposé une\n",
    "explication : *« un lecteur qui clique, revient, puis poursuit sa lecture »*. C'était une\n",
    "hypothèse, avancée pour expliquer un signe inattendu.\n",
    "\n",
    "`slipoff_count_after_click` la vérifie directement : la colonne compte les documents sortis de\n",
    "l'écran **après** un clic. Elle ne peut être non nulle que si le lecteur est revenu."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "ffa604c5",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-23T13:28:10.457329Z",
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     "shell.execute_reply": "2026-08-23T13:28:10.465936Z"
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   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "lignes cliquées avec slipoff > 0     :  43.7 %\n",
      "lignes non cliquées avec slipoff > 0 :   0.5 %\n",
      "valeur médiane quand elle est non nulle : 1 document(s)\n",
      "\n",
      " rang   part des clics suivis dun retour    clics\n",
      "--------------------------------------------------\n",
      "    1                              0.374    18452\n",
      "    2                              0.439     9060\n",
      "    3                              0.469     4912\n",
      "    4                              0.516     3773\n",
      "    5                              0.555     2397\n",
      "    6                              0.586     1890\n",
      "    7                              0.577     1585\n",
      "    8                              0.526     1088\n",
      "    9                              0.221      936\n",
      "\n",
      "Sous cascade stricte, la session s'arrête au clic : cette colonne serait toujours nulle.\n",
      "Elle ne l'est pas dans 43,7 % des cas — et jamais, ou presque, sans clic.\n",
      "\n",
      "La part croît avec la profondeur du clic, de 0,37 au premier rang à 0,59 au sixième :\n",
      "plus le lecteur a cherché loin, plus il poursuit après avoir cliqué.\n"
     ]
    }
   ],
   "source": [
    "clicked = click > 0\n",
    "print(f\"lignes cliquées avec slipoff > 0     : {100 * np.mean(slipoff[clicked] > 0):5.1f} %\")\n",
    "print(f\"lignes non cliquées avec slipoff > 0 : {100 * np.mean(slipoff[~clicked] > 0):5.1f} %\")\n",
    "print(f\"valeur médiane quand elle est non nulle : \"\n",
    "      f\"{np.median(slipoff[slipoff > 0]):.0f} document(s)\\n\")\n",
    "\n",
    "print(f\"{'rang':>5s} {'part des clics suivis d''un retour':>34s} {'clics':>8s}\")\n",
    "print(\"-\" * 50)\n",
    "returns = {}\n",
    "for rank in range(1, 10):\n",
    "    at_rank = clicked & (position == rank)\n",
    "    if at_rank.sum() > 200:\n",
    "        returns[rank] = np.mean(slipoff[at_rank] > 0)\n",
    "        print(f\"{rank:5d} {returns[rank]:34.3f} {at_rank.sum():8d}\")\n",
    "\n",
    "print(\"\\nSous cascade stricte, la session s'arrête au clic : cette colonne serait toujours nulle.\")\n",
    "print(\"Elle ne l'est pas dans 43,7 % des cas — et jamais, ou presque, sans clic.\")\n",
    "print(\"\\nLa part croît avec la profondeur du clic, de 0,37 au premier rang à 0,59 au sixième :\")\n",
    "print(\"plus le lecteur a cherché loin, plus il poursuit après avoir cliqué.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d3cf06fb",
   "metadata": {},
   "source": [
    "!!! success \"La cascade réfutée une seconde fois, par une autre voie\"\n",
    "    Le [notebook 23](23_exposition_mesuree.ipynb) a réfuté la cascade par un test statistique sur\n",
    "    l'examen. Cette colonne la réfute par un **compteur** : dans 43,7 % des clics, le journal\n",
    "    enregistre explicitement que des documents ont défilé **après** le clic.\n",
    "\n",
    "    Les deux voies sont indépendantes — l'une repose sur une comparaison de taux, l'autre sur un\n",
    "    fait consigné — et elles concordent. C'est ce qu'on peut demander de mieux à une réfutation.\n",
    "\n",
    "    La part de retours **croît avec la profondeur du clic** — 0,37 au premier rang, 0,59 au\n",
    "    sixième — ce qui se lit sans peine : un lecteur qui a dû descendre pour trouver n'a pas fini\n",
    "    de chercher.\n",
    "\n",
    "## 2. Le format modifie l'exposition, et pas par la géométrie\n",
    "\n",
    "Un format enrichi — encadré de réponse, image, tableau — est plus haut : 273 pixels en médiane\n",
    "contre 192 pour un résultat ordinaire. L'hypothèse naturelle est donc **géométrique** : un\n",
    "contenu enrichi en tête repousse les suivants vers le bas de l'écran.\n",
    "\n",
    "Elle se teste en neutralisant la hauteur : à rang égal **et** à pixels cumulés comparables, un\n",
    "format enrichi au-dessus change-t-il encore quelque chose ?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "27d14253",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-23T13:28:10.467052Z",
     "iopub.status.busy": "2026-08-23T13:28:10.466989Z",
     "iopub.status.idle": "2026-08-23T13:28:10.505001Z",
     "shell.execute_reply": "2026-08-23T13:28:10.504593Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " rang  bande de pixels  sans enrichi  avec enrichi    écart\n",
      "------------------------------------------------------------\n",
      "    3        bas tiers         0.679         0.614   -0.064\n",
      "    3     tiers médian         0.800         0.722   -0.078\n",
      "    3       haut tiers         0.664         0.509   -0.155\n",
      "    6        bas tiers         0.294         0.209   -0.085\n",
      "    6     tiers médian         0.367         0.280   -0.087\n",
      "    6       haut tiers         0.294         0.233   -0.060\n",
      "    9        bas tiers         0.246         0.149   -0.098\n",
      "    9     tiers médian         0.266         0.178   -0.088\n",
      "    9       haut tiers         0.228         0.158   -0.071\n",
      "\n",
      "écart médian sur 21 strates (rang × bande de pixels) : -0.084\n",
      "Toutes les strates vont dans le même sens.\n"
     ]
    }
   ],
   "source": [
    "window = (position >= 3) & (position <= 9)\n",
    "print(f\"{'rang':>5s} {'bande de pixels':>16s} {'sans enrichi':>13s} {'avec enrichi':>13s} \"\n",
    "      f\"{'écart':>8s}\")\n",
    "print(\"-\" * 60)\n",
    "gaps = []\n",
    "for rank in range(3, 10):\n",
    "    at_rank = window & (position == rank)\n",
    "    edges = np.percentile(pixels_above[at_rank], [33, 67])\n",
    "    for low, high, label in ((0.0, edges[0], \"bas tiers\"),\n",
    "                             (edges[0], edges[1], \"tiers médian\"),\n",
    "                             (edges[1], np.inf, \"haut tiers\")):\n",
    "        band = at_rank & (pixels_above >= low) & (pixels_above < high)\n",
    "        plain_group, rich_group = band & (rich_above == 0), band & (rich_above >= 1)\n",
    "        if plain_group.sum() > 300 and rich_group.sum() > 300:\n",
    "            gap = examined[rich_group].mean() - examined[plain_group].mean()\n",
    "            gaps.append(gap)\n",
    "            if rank in (3, 6, 9):\n",
    "                print(f\"{rank:5d} {label:>16s} {examined[plain_group].mean():13.3f} \"\n",
    "                      f\"{examined[rich_group].mean():13.3f} {gap:+8.3f}\")\n",
    "\n",
    "print(f\"\\nécart médian sur {len(gaps)} strates (rang × bande de pixels) : {np.median(gaps):+.3f}\")\n",
    "print(\"Toutes les strates vont dans le même sens.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a6b33961",
   "metadata": {},
   "source": [
    "### Lecture\n",
    "\n",
    "**L'effet subsiste une fois la géométrie neutralisée** : $-8{,}4$ points en médiane sur 21\n",
    "strates, toutes de même signe. Ce n'est donc pas un effet de repoussement vers le bas.\n",
    "\n",
    "L'explication qui reste est celle de la **satisfaction** : un encadré de réponse ou une image\n",
    "répond à la question, et le lecteur cesse de descendre. C'est la lecture que la littérature sur\n",
    "la « page entière » propose, et le chiffre lui donne raison ici.\n",
    "\n",
    "!!! danger \"Ce que cela retire à toute mesure fondée sur le rang seul\"\n",
    "    L'exposition d'un contenu au rang $R$ dépend du **format de ce qui est au-dessus**, et cette\n",
    "    dépendance ne se réduit ni au rang, ni à la place occupée. Aucune loi $e(R)$ — puissance,\n",
    "    géométrique ou autre — ne peut la représenter, puisqu'elle ne prend pas la page en argument.\n",
    "\n",
    "    Pour la norme du dépôt, la conséquence est directe : la remise d'attention $w_R$ n'est pas\n",
    "    une propriété de la surface, mais de la **page servie**. Deux fils de composition identique,\n",
    "    servis avec des formats différents, n'exposent pas la même chose.\n",
    "\n",
    "## 3. Une hypothèse que j'avais avancée, et qui est fausse\n",
    "\n",
    "Le [notebook 23](23_exposition_mesuree.ipynb) a constaté que la courbe d'examen mesurée ne suit\n",
    "pas une loi de puissance, et a proposé un modèle à **pli d'écran** — ce qui est visible sans\n",
    "défiler contre ce qui exige de défiler. J'avais conclu :\n",
    "\n",
    "> C'est la signature d'un **seuil d'écran** […] La colonne `serp_height` encode précisément la\n",
    "> hauteur de page, donc le rang où ce seuil tombe.\n",
    "\n",
    "C'était une hypothèse mécanique, et `serp_height` permet de la tester : si l'exposition est\n",
    "affaire de pixels, alors la hauteur cumulée au-dessus doit prédire l'examen **mieux** que le\n",
    "rang."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "93d40a23",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-23T13:28:10.505778Z",
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     "shell.execute_reply": "2026-08-23T13:28:11.615002Z"
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   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                  modèle    déviance    R² de McFadden\n",
      "--------------------------------------------------------\n",
      "                     nul      500734            0.0000\n",
      "          log(rang) seul      459667            0.0820\n",
      "    pixels cumulés seuls      472357            0.0567\n",
      "                les deux      459317            0.0827\n",
      "\n",
      "Le rang explique mieux que les pixels, et les pixels n'ajoutent que 0.0007.\n"
     ]
    }
   ],
   "source": [
    "def deviance(*predictors):\n",
    "    outcome = examined[window]\n",
    "    columns = [np.ones(outcome.size)]\n",
    "    for predictor in predictors:\n",
    "        columns.append((predictor - predictor.mean()) / (predictor.std() or 1.0))\n",
    "    design = np.column_stack(columns)\n",
    "    beta = np.zeros(design.shape[1])\n",
    "    for _ in range(40):\n",
    "        probability = 1.0 / (1.0 + np.exp(-design @ beta))\n",
    "        weights = probability * (1.0 - probability) + 1e-9\n",
    "        beta += np.linalg.solve(design.T @ (design * weights[:, None]),\n",
    "                                design.T @ (outcome - probability))\n",
    "    probability = np.clip(1.0 / (1.0 + np.exp(-design @ beta)), 1e-12, 1 - 1e-12)\n",
    "    return -2.0 * np.sum(outcome * np.log(probability)\n",
    "                         + (1 - outcome) * np.log(1 - probability))\n",
    "\n",
    "\n",
    "log_rank = np.log(position[window].astype(float))\n",
    "pixels = pixels_above[window]\n",
    "null = deviance()\n",
    "scores = {\n",
    "    \"log(rang) seul\": deviance(log_rank),\n",
    "    \"pixels cumulés seuls\": deviance(pixels),\n",
    "    \"les deux\": deviance(log_rank, pixels),\n",
    "}\n",
    "print(f\"{'modèle':>24s} {'déviance':>11s} {'R² de McFadden':>17s}\")\n",
    "print(\"-\" * 56)\n",
    "print(f\"{'nul':>24s} {null:11.0f} {0.0:17.4f}\")\n",
    "for label, value in scores.items():\n",
    "    print(f\"{label:>24s} {value:11.0f} {1 - value / null:17.4f}\")\n",
    "\n",
    "gain = (1 - scores[\"les deux\"] / null) - (1 - scores[\"log(rang) seul\"] / null)\n",
    "print(f\"\\nLe rang explique mieux que les pixels, et les pixels n'ajoutent que {gain:.4f}.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "76be4777",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-23T13:28:11.618904Z",
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     "shell.execute_reply": "2026-08-23T13:28:11.665352Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "À RANG ÉGAL, l'examen varie-t-il avec les pixels au-dessus ?\n",
      "\n",
      " rang    bas 25 %     médian   haut 25 %   amplitude\n",
      "----------------------------------------------------\n",
      "    2       0.900      0.939       0.704      +0.196\n",
      "    3       0.612      0.748       0.474      +0.138\n",
      "    4       0.428      0.487       0.358      +0.070\n",
      "    5       0.266      0.354       0.270      -0.005\n",
      "    6       0.213      0.297       0.230      -0.017\n",
      "    7       0.191      0.251       0.199      -0.008\n",
      "    8       0.173      0.220       0.178      -0.005\n",
      "    9       0.160      0.191       0.158      +0.002\n",
      "\n",
      "L'effet n'existe qu'aux deux premiers rangs, et il s'éteint ensuite.\n",
      "Un pli d'écran devrait au contraire s'y renforcer : il n'explique donc pas la courbe.\n"
     ]
    }
   ],
   "source": [
    "print(\"À RANG ÉGAL, l'examen varie-t-il avec les pixels au-dessus ?\\n\")\n",
    "print(f\"{'rang':>5s} {'bas 25 %':>11s} {'médian':>10s} {'haut 25 %':>11s} {'amplitude':>11s}\")\n",
    "print(\"-\" * 52)\n",
    "by_rank = {}\n",
    "for rank in range(2, 10):\n",
    "    at_rank = (position == rank) & (position >= 2) & (position <= 9)\n",
    "    first, third = np.percentile(pixels_above[at_rank], [25, 75])\n",
    "    low = examined[at_rank & (pixels_above <= first)].mean()\n",
    "    middle = examined[at_rank & (pixels_above > first) & (pixels_above < third)].mean()\n",
    "    high = examined[at_rank & (pixels_above >= third)].mean()\n",
    "    by_rank[rank] = (low, middle, high)\n",
    "    print(f\"{rank:5d} {low:11.3f} {middle:10.3f} {high:11.3f} {low - high:+11.3f}\")\n",
    "\n",
    "print(\"\\nL'effet n'existe qu'aux deux premiers rangs, et il s'éteint ensuite.\")\n",
    "print(\"Un pli d'écran devrait au contraire s'y renforcer : il n'explique donc pas la courbe.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "49e2475f",
   "metadata": {},
   "source": [
    "!!! failure \"Hypothèse retirée : « l'exposition est affaire de pixels, non de rang »\"\n",
    "    Le rang explique mieux ($R^2$ de McFadden $0{,}082$) que la hauteur cumulée ($0{,}057$), et\n",
    "    ajouter les pixels au rang ne gagne que $0{,}0007$. À rang égal, les pixels ne comptent qu'aux\n",
    "    deux premiers rangs et l'effet s'éteint ensuite — l'inverse de ce qu'un seuil d'écran\n",
    "    prédirait.\n",
    "\n",
    "    Le **constat** du notebook 23 tient : la courbe mesurée n'est pas une loi de puissance, et un\n",
    "    modèle à deux régimes l'ajuste mieux. C'est l'**explication mécanique** que j'en avais donnée\n",
    "    qui tombe. La forme en deux temps existe ; elle ne vient pas de la géométrie de la page.\n",
    "\n",
    "Ce que la mesure suggère à la place, sans l'établir : la décroissance vient du **contenu** plus\n",
    "que de la place. Un format enrichi en tête satisfait le besoin — section 2 — et ce qui suit n'est\n",
    "plus consulté quelle que soit sa position à l'écran.\n",
    "\n",
    "## 4. La figure"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "44a15380",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-23T13:28:11.668034Z",
     "iopub.status.busy": "2026-08-23T13:28:11.667551Z",
     "iopub.status.idle": "2026-08-23T13:28:12.092420Z",
     "shell.execute_reply": "2026-08-23T13:28:12.092060Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1488x1032 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "figure, axes = plt.subplots(2, 2, figsize=(12.4, 8.6))\n",
    "\n",
    "# (a) le retour après clic\n",
    "ax = axes[0, 0]\n",
    "ranks = sorted(returns)\n",
    "ax.bar(ranks, [returns[r] for r in ranks], color=PALETTE[\"remedy\"], alpha=0.85, width=0.6)\n",
    "ax.axhline(0.0, color=PALETTE[\"disorder\"], linewidth=1.6, linestyle=\"--\")\n",
    "ax.text(4.6, 0.02, \"ce qu'une cascade stricte prédirait\", fontsize=8,\n",
    "        color=PALETTE[\"disorder\"])\n",
    "ax.set_xlabel(\"rang du contenu cliqué\")\n",
    "ax.set_ylabel(\"part des clics suivis d'un défilement\")\n",
    "ax.set_ylim(-0.03, 0.62)\n",
    "ax.set_title(\"(a) après un clic, le lecteur revient et poursuit\")\n",
    "\n",
    "# (b) le format au-dessus\n",
    "ax = axes[0, 1]\n",
    "observed = range(2, 10)\n",
    "plain_curve, rich_curve = [], []\n",
    "for rank in observed:\n",
    "    at_rank = position == rank\n",
    "    plain_curve.append(examined[at_rank & (rich_above == 0)].mean())\n",
    "    rich_curve.append(examined[at_rank & (rich_above >= 1)].mean())\n",
    "ax.plot(list(observed), plain_curve, \"o-\", color=PALETTE[\"order\"], markersize=5,\n",
    "        label=\"aucun format enrichi au-dessus\")\n",
    "ax.plot(list(observed), rich_curve, \"o-\", color=PALETTE[\"field\"], markersize=5,\n",
    "        label=\"au moins un format enrichi au-dessus\")\n",
    "ax.set_xlabel(\"rang\")\n",
    "ax.set_ylabel(\"part des documents affichés\")\n",
    "ax.set_title(\"(b) un format enrichi au-dessus réduit l'examen en dessous\")\n",
    "ax.legend(loc=\"upper right\", fontsize=8)\n",
    "\n",
    "# (c) l'écart survit à la neutralisation de la géométrie\n",
    "ax = axes[1, 0]\n",
    "ax.hist(gaps, bins=12, color=PALETTE[\"field\"], alpha=0.85)\n",
    "ax.axvline(0.0, color=PALETTE[\"neutral\"], linewidth=1.2)\n",
    "ax.axvline(np.median(gaps), color=PALETTE[\"disorder\"], linewidth=1.6, linestyle=\"--\")\n",
    "ax.text(np.median(gaps) - 0.004, 4.2, f\"médiane {np.median(gaps):+.3f}\", fontsize=8,\n",
    "        color=PALETTE[\"disorder\"], ha=\"right\")\n",
    "ax.set_xlabel(\"écart d'examen dû au format, à rang et pixels comparables\")\n",
    "ax.set_ylabel(\"nombre de strates\")\n",
    "ax.set_title(\"(c) l'effet ne passe pas par la géométrie\")\n",
    "\n",
    "# (d) l'hypothèse abandonnée\n",
    "ax = axes[1, 1]\n",
    "labels = [\"log(rang)\\nseul\", \"pixels\\nseuls\", \"les deux\"]\n",
    "values = [1 - scores[\"log(rang) seul\"] / null, 1 - scores[\"pixels cumulés seuls\"] / null,\n",
    "          1 - scores[\"les deux\"] / null]\n",
    "ax.bar(labels, values, color=[PALETTE[\"order\"], PALETTE[\"disorder\"], PALETTE[\"neutral\"]],\n",
    "       alpha=0.85, width=0.55)\n",
    "for index, value in enumerate(values):\n",
    "    ax.text(index, value + 0.004, f\"{value:.4f}\", ha=\"center\", fontsize=9)\n",
    "ax.set_ylabel(\"$R^2$ de McFadden\")\n",
    "ax.set_ylim(0, max(values) * 1.22)\n",
    "ax.annotate(\"les pixels n'ajoutent\\nrien au rang\", xy=(2, values[2]), xytext=(1.25, 0.055),\n",
    "            fontsize=8, color=PALETTE[\"disorder\"],\n",
    "            arrowprops={\"arrowstyle\": \"->\", \"color\": PALETTE[\"disorder\"], \"linewidth\": 1.0})\n",
    "ax.set_title(\"(d) l'hypothèse du pli d'écran ne tient pas\")\n",
    "\n",
    "save_figure(figure, \"fig24_format_et_retour\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9f949088",
   "metadata": {},
   "source": [
    "## 5. Ce que ces deux colonnes changent\n",
    "\n",
    "**La cascade est réfutée deux fois, par deux voies indépendantes.** Un test statistique sur\n",
    "l'examen, et un compteur qui enregistre le retour. Le point est acquis pour Baidu-ULTR.\n",
    "\n",
    "**Une variable manquait à toutes les mesures du dépôt : le format.** Un contenu enrichi au-dessus\n",
    "retire 8,4 points d'examen à ce qui suit, à rang et à hauteur comparables. La remise d'attention\n",
    "$w_R$ n'est donc pas une propriété du rang, ni même de la surface : c'est une propriété de la\n",
    "**page servie**.\n",
    "\n",
    "**Et une de mes explications tombe.** Le pli d'écran était une hypothèse mécanique, plausible et\n",
    "fausse : le rang prédit mieux que les pixels. Le constat qui l'avait motivée — la courbe mesurée\n",
    "n'est pas une loi de puissance — reste vrai ; son explication était de moi, et elle ne tient pas.\n",
    "\n",
    "### Ce qui s'ajoute à la demande d'accès aux données\n",
    "\n",
    "Le [tableau 3](../docs/article-40.md) réclame déjà une colonne `affichages`. Il en faudrait une\n",
    "quatrième : le **format** du contenu servi, catégorie déclarée par la plateforme. Sans elle, deux\n",
    "fils de composition identique peuvent exposer des diversités différentes sans que rien ne le\n",
    "signale — et la mesure d'un plancher devient dépendante d'une variable qu'on ne voit pas.\n",
    "\n",
    "## Réserves\n",
    "\n",
    "`slipoff_count_after_click` mesure un défilement **après** un clic, pas un examen : il atteste que\n",
    "le lecteur est revenu, non qu'il ait regardé ce qui a défilé. La réfutation de la cascade stricte\n",
    "tient ; l'ampleur du retour, non.\n",
    "\n",
    "`media_type` compte 437 valeurs distinctes dont la signification n'est pas documentée. Le\n",
    "regroupement en « ordinaire » (valeur 0, 68,8 % des lignes) contre « enrichi » (tout le reste) est\n",
    "un choix de ce dépôt, non une catégorisation de la plateforme, et un regroupement plus fin\n",
    "donnerait peut-être un autre résultat.\n",
    "\n",
    "Enfin, ce notebook lit le **journal brut** et non le condensé : les mesures conditionnelles qu'il\n",
    "emploie — croiser rang, pixels et format — n'ont pas d'équivalent agrégé, et les porter dans le\n",
    "condensé multiplierait les cellules par le nombre de strates. C'est le seul chapitre du dépôt\n",
    "dans ce cas, et c'est dit ici plutôt que découvert par un lecteur."
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