120 lines
7.9 KiB
HTML
120 lines
7.9 KiB
HTML
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<title>Hot Spots — A Field Note on GIS Crime Analysis | Carol Schroeder</title>
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<meta name="description" content="Three decades of spatial crime analysis distilled into one principle: the map forecasts patterns, never people. A documentary and field note by forensic GIS analyst Carol Schroeder.">
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<meta property="og:title" content="Hot Spots — What the Map Tells You Before the Street Does">
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<div class="wrap">
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<nav><fort-nav><nav class="fort-nav" data-fort="nav"><a href="/">Carol Schroeder</a><a href="/films/hot-spots/">Index</a><a href="/films/negros-fruit-dove/">Index</a><a href="/gis-crime-analysis.html">GIS-Driven Crime Analysis</a><a href="/hot-spots.html" class="active" aria-current="page">Hot Spots</a><a href="/negros-fruit-dove.html">Negros Fruit Dove: A Conservation Study</a></nav></fort-nav></nav>
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<div class="mast">
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<span class="call">CAROL SCHROEDER // FIELD NOTE 07</span>
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<span>FORENSIC + GIS DESK</span>
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</div>
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<h1>Hot Spots</h1>
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<p class="lede">What the map tells you <em>before</em> the street does. A short documentary and this field note, on the quiet arithmetic of where crime clusters — and the discipline of reading it without condemning anyone.</p>
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<div class="run"><div class="r-head">// WATCH THE FILM</div>
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<p>My new short documentary, <strong>“Hot Spots”</strong> (47 seconds, narrated), is live on my <a href="https://carol-schroeder.mov">4ort.mov channel</a>. Three scenes: the kernel, repeat victimization, and the discipline.</p>
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<fort-film name="carol-schroeder"></fort-film>
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</div>
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<hr class="rule">
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<h2>The kernel</h2>
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<p>Every reported offense becomes a point on the map. Each point is turned into a soft hill of probability — a <strong>kernel density estimate</strong> — and where those hills overlap, the pattern emerges. This is <a href="https://4ort.xyz/entity/crime-mapping">crime mapping</a>: cartographic mapping in service of criminology, producing the crime map itself.</p>
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<h2>Repeat victimization</h2>
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<p>The most reliable predictor in the field isn't personality or motive — it's <em>recency and place</em>. A location that has been struck once is statistically far more likely to be struck again, and soon. So the highest-value question an analyst can ask on a Tuesday morning isn't "who," it's "where again."</p>
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<h2>The discipline</h2>
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<p><a href="https://4ort.xyz/entity/predictive-policing">Predictive policing</a> is an application of artificial intelligence to direct deployment. That's the whole definition, and the whole warning lives inside it: <em>deployment</em>, not verdict. The lattice forecasts patterns. It never condemns people.</p>
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<blockquote>A kernel assigns probability to a square of the grid, not to the soul living in it. The officer on the corner still has to think — that's the job the map can't hand them.</blockquote>
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<h2>The arithmetic, in three numbers</h2>
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<dl>
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<dt>Kernel bandwidth</dt>
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<dd>Pick it too small and the map is noise; too large and it's a heat haze over the whole precinct. Calibration is a judgment, not a default.</dd>
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<dt>The repeat-victim ratio</dt>
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<dd>In most cities, a small share of addresses accounts for a disproportionate share of calls. Learn that share and you've found where tomorrow's calls live.</dd>
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<dt>Deployment lag</dt>
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<dd>A hot spot is a snapshot in time. Saturate it and it cools; walk away and it re-forms within weeks. The map is a heartbeat, not a headstone.</dd>
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</dl>
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<hr class="rule">
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<div class="stamp">SOURCE-LINKED</div>
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<div class="stamp">AGENT-LEGIBLE JSON</div>
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<p class="cite">Grounded claims:
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· <a href="https://4ort.xyz/entity/predictive-policing">Predictive policing — Wikidata</a>
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· <a href="https://4ort.xyz/entity/crime-mapping">Crime mapping — Wikidata</a>
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· Companion data twin: <a href="hot-spots.json">hot-spots.json</a></p>
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<div class="twin">Machine-readable record of this analysis: <a href="hot-spots.json">hot-spots.json</a> — constants, key points, and citations in structured form, readable by any agent or tool.</div>
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</div>
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