# West Campus: safety, place and time

Research edition • November 2, 2026 • Complete occurrence years 2016–2025; population comparison 2020–2024. Street detail has a shorter coverage window and separate time-quality checks.

West Campus’s record contains two truths that a single safety grade obscures. Within the defined census-block-group footprint, Austin police recorded more theft, burglary and auto-theft reports per estimated resident than the city average during 2020–2024: 42.7 versus 34.3 annually per 1,000. In four selected serious categories—murder, rape, robbery and aggravated assault—the corresponding rates were 2.0 versus 4.3. These directions survive the tested West Campus boundary definitions. They describe recorded neighborhood burden; they do not give a student’s probability of being attacked on a walk.

The strongest explanatory finding is a denominator reversal. West Campus had 3.3 times Riverside’s property-report density per square kilometer, yet a lower property-report rate per resident. A student can encounter more reminders of crime nearby while the resident-normalized record is lower. Density concentrates both people and their losses. This is an arithmetic explanation of two apparently conflicting descriptions, without establishing that density itself causes or prevents crime.

The most consequential data discovery concerns the clock. Across 42,253 selected city map records, a conservative empirical linkage matched 40,023 to the incident table using offense code, reporting minute and the block group containing the published point, with one-to-one checks. For 31,489 of those linked records, the map’s fields labeled “occurrence” differ from the incident table’s actual occurrence date or time. They match the reporting timestamp. An unexamined hourly street map would therefore largely show when reports were filed. The report preserves this audit and treats linked occurrence times separately.

The street concentration story is also weaker than the initial hypothesis. Among 2,181 West Campus property reports linked to recorded occurrences in 2022–2025, the ten busiest blocks account for 591, or 27.1%. Ten blocks selected using only 2022–2023 capture 21.5% of linked reports in 2024–2025. Those are useful places to investigate, but the evidence does not support saying a handful of permanent danger spots explains most incidents.

What is complete: a reproducible ten-year APD incident census; explicit neighborhood/population crosswalks; raw counts and rates; recorded-hour diagnostics; audited recent street records; a cross-source timestamp linkage; lighting-request data; and an evidence and methods audit. What remains unavailable: six additional years of verified street locations, a complete deduplicated APD–UTPD event census, historical resident exposure, and the stated 161-building dataset. The final section specifies the records needed to resolve those gaps.

## Start where existing work stops

There is already substantial prior work. The Texas Tribune mapped 165 selected UTPD incidents involving non-affiliates in early 2016 and warned about agency coverage. The Daily Texan has reported the gap between student experience and official totals, property crime, lighting and route choices. Austin already offers CrimeViewer, and commercial sites already publish neighborhood crime maps. A 2017 city lighting initiative explicitly included crime analysis. This project should not be promoted as the first West Campus crime map or as proof that nobody has examined the data. [S2, S10, S11, S13, S23]

What the sampled public answers usually fail to supply together is a fixed time window, a clearly drawn neighborhood, a consistent offense definition, a matched population denominator, an agency-coverage account and a check on the meaning of the clock. The landscape review is targeted and non-exhaustive. It identifies a research contribution; it does not establish universal novelty or a stable search-engine ranking.

The current incident export also changes the feasible scope. Its live schema has 19 fields and provides a census block group, with no address or latitude/longitude columns. A stale attached field dictionary describes a richer historical schema. The map service supplies recent block locations, but not the requested ten complete historical years. The ten-year layer therefore remains at block-group resolution, while the street-hour layer is explicitly a linked 2022–2025 subset. No historical block-group total is assigned to an invented corner. [S1, S3, S4]

One sampled commercial page illustrates why a grade cannot substitute for that work. DoorProfit’s West Campus page combined a B+ description with a statement that the neighborhood was safer than only 11% of Austin neighborhoods. Its displayed index of 172 against Austin’s 83 was described as 89% higher, although that pair implies about 107%. These are internal consistency problems on the retrieved page, not independent measurements of crime. Other existing products also supply useful maps, so their presence should be acknowledged rather than erased. [S12, S13]

The student questions are more specific than “safe.” One Reddit discussion asks about a woman walking home alone; another asks where to protect a parked car. The Daily Texan records how incidents and fear restrict movement. These establish decisions worth answering, not the proportion of students who fear a particular offense. The proposed claim that property crime occupies “almost none of the fear” should be dropped: students explicitly ask about cars, bikes and access-controlled parking. A representative survey would be needed to quantify the fear–record relationship. [S11, S14, S15]

## The structure: harm, exposure and observation

A useful safety measure needs three things: the harm of interest, the exposure creating an opportunity for that harm, and the process that makes the harm visible in the record. Theft from a parked car calls for a denominator such as cars parked or parking-hours. Assault during a walk calls for people present and time spent on the route. A neighborhood’s resident population is useful for comparing recorded burden, but visitors, workers, customers and students moving through the area also generate exposure.

The observed total is also shaped by reporting and recording. An event may be unreported, reported to APD, reported to UTPD, disclosed through a university channel, classified differently later or omitted from a public location feed. A patrol expansion can affect detection and which agency holds the report as well as underlying harm. These mechanisms are alternatives to test; the available data do not identify their separate magnitudes.

This frame avoids treating student fear as an arithmetic error. Severity, harassment, a previous experience and the availability of a ride can rationally matter even when selected serious reports are infrequent. Conversely, a dense field of map dots does not by itself establish high individual risk. The defensible product separates these questions and exposes the denominator rather than collapsing them into a color or grade.

## The fair comparison

The main comparison uses APD occurrences during 2020–2024 and the ACS 2020–2024 five-year population estimate for exactly the same selected whole census block groups. The calculation is reports divided by five, divided by estimated residents, multiplied by 1,000. It is labeled average annual APD reports per 1,000 estimated residents. The city baseline uses reports assigned to Austin council districts 1–10 and the ACS Austin city population of 979,539. [S1, S5–S8]

| Study footprint | Population | Property count | Property /1,000/year | Serious count | Serious /1,000/year |
| :---- | :---- | :---- | :---- | :---- | :---- |
| West Campus | 15,025 | 3,208 | 42.7 | 153 | 2.0 |
| North University core | 4,714 | 919 | 39.0 | 40 | 1.7 |
| Hyde Park | 6,903 | 859 | 24.9 | 44 | 1.3 |
| Riverside / Parker Lane / Pleasant Valley | 35,044 | 9,681 | 55.3 | 1,717 | 9.8 |
| Blackland / Cherrywood / Chestnut | 6,960 | 1,211 | 34.8 | 110 | 3.2 |
| Austin baseline | 979,539 | 168,228 | 34.3 | 21,265 | 4.3 |

Property here means theft, burglary and auto theft. Serious means murder, rape, robbery and aggravated assault. The APD dataset retains the highest offense for an incident; neither column counts every offense or every victim. Criminal mischief, simple assault, harassment and many other recorded harms sit outside these two selected families. “Other” is not a synonym for harmless or noncriminal. [S1]

![Figure 1: Aligned bars compare annual property and four-category serious reports per 1,000 residents across five study areas and Austin during 2020–2024. West Campus has 42.7 property reports and 2.0 serious-category reports per 1,000 estimated residents annually.](/research/deep-research/figures/crime-figure-1-neighborhood-rates.svg)

Figure 1. Counts and denominators are preserved in the audit tables. The city and neighborhood rates describe APD reports, with distinct agency and exposure limitations. The graphic shows point estimates; the boundary and population qualifications below still apply.

The main West Campus footprint has an estimated 15,025 residents for this period. That should not be silently replaced with an approximate contemporary population of 20,000: the geography and period differ. Population uncertainty alone gives an approximate West Campus property-rate range of 38.8–47.4 and serious-category range of 1.9–2.3. These are denominator sensitivities, not comprehensive confidence intervals for crime or safety.

North Campus requires a prominent qualification. North University alone gives 39.0 property reports per 1,000, below West Campus’s 42.7. Expanding North Campus to include Heritage and Hancock gives 55.8 under the main rule, above West Campus. Tested selection rules for that expanded definition give approximately 50.6–55.8. A blanket claim that one of these two neighborhoods has more property crime depends on which North Campus was meant.

The Riverside serious-category difference is more stable: the broad three-area footprint gives 9.8, and the stricter geographic selection gives 9.5. Its property estimate ranges from 45.2 to 55.3 across those selections. Hyde Park remains below the city in the tested comparisons, but small serious counts and population uncertainty argue against a confident “safest” ranking. The East study area’s property estimate ranges from 30.9 to 37.1, crossing the city’s 34.3; its position relative to Austin is unresolved by the boundary test.

## Draw the neighborhood before ranking it

The West Campus target combines City planning polygons 69, 13 and 24, excluding Heritage/78. It approximates the area between MLK and 29th and between Guadalupe and Lamar. North University/36 supplies the core North Campus definition. Hyde Park is polygon 16. Riverside combines Riverside/27, Parker Lane/71 and Pleasant Valley/82. The East study area combines Blackland/34, Cherrywood/52 and Chestnut/72; it excludes Mueller and is explicitly a study definition. The city’s historical planning descriptions support the distinction between Heritage north of 29th and the retained area to its south. [S6, S9]

For ten-year rates, a block group is included whole when at least half its polygon area lies inside the target. Counts are never spread proportionally across a cut polygon. This keeps each numerator and population denominator aligned, at the cost of an imperfect neighborhood fit. Alternative rules use 90% overlap, 10% overlap and the Census internal point. The source polygons and every inclusion decision are provided.

![Figure 2: Five geographic maps compare the exact City planning-area study targets with the whole Census 2022 block groups selected for rate calculations. West Campus covers 94.5% of its target, while only 79.1% of the East target is covered.](/research/deep-research/figures/crime-figure-2-boundaries.svg)

Figure 2. Dark outlines are the target study boundaries; rust areas are the whole census block groups used for rates. Each panel has its own scale. These overlap percentages measure polygon area, not residents. The supplied GeoJSON and provenance file preserve the cited geometry sources, vintages, study IDs and retrieval hashes.

The West Campus selection covers 94.5% of target area, and 90.1% of its selected area lies inside the target. North University fits almost exactly. The East selection covers only 79.1% of intended land; Hyde Park’s selected footprint is only 77.9% inside its target. Those mismatches are material. They are why the report publishes sensitivity ranges and avoids small-area league tables for Blackland or Cherrywood alone.

## Density changes the answer without changing a single report

| 2020–2024 property reports | West Campus | Riverside study area |
| :---- | :---- | :---- |
| Average per year | 641.6 | 1,936.2 |
| Per 1,000 estimated residents per year | 42.7 | 55.3 |
| Per square kilometer per year | 440.5 | 135.1 |

West Campus contains fewer property reports per resident than the Riverside study area, but 3.26 times as many per square kilometer. Its census-block-group footprint is about 1.46 square kilometers; Riverside’s is about 14.33. A map of nearby events and a resident-normalized comparison answer different questions. Both can be numerically correct.

The serious-category comparison also changes with the denominator. West Campus has 21.0 annual serious-category reports per square kilometer and Riverside 24.0—much closer than their per-resident rates of 2.0 and 9.8. Neither area density nor residential population measures pedestrian exposure. The finding explains why geographic proximity to reports is a poor substitute for estimating the risk of a particular journey; it does not prove “eyes on the street” won or lost.

## Ten years of counts: no simple tower-era story

![Figure 3: Separate line charts show West Campus annual property counts and four-category serious counts from 2016 through 2025. The ten-year totals are 6,056 and 325; the two panels use different count scales.](/research/deep-research/figures/crime-figure-3-annual-counts.svg)

Figure 3. Fixed West Campus census-block-group footprint. The ten-year property total is 6,056; the four serious-category total is 325. The shaded period marks 2020–2021 without assigning a causal explanation. These are raw counts, and the two panels use separate scales.

Property counts run from 450 in 2017 to 811 in 2020; they were 647 in 2016, 528 in 2023 and 669 in 2025. The four serious-category counts range from 25 to 39 a year. This is not a steady rise or a steady decline. It also does not establish the direction of change per resident, because annual population and occupancy have not been reconstructed for the same historical footprint.

Two institutional changes matter. APD changed nonemergency response/reporting practices in October 2021, while UTPD said its own service would remain unchanged. UTPD then established a dedicated West Campus patrol district effective August 4, 2025 and expanded westward to Lamar. Either change can affect what appears in an APD-only series. The report shows 2025 separately in persistence checks and does not attribute a change to towers, lighting or patrol without a design that distinguishes these mechanisms. [S18, S19]

Across all 11,736 West Campus APD records in 2016–2025, the three property categories account for 51.6%; the four serious categories account for 2.8%. The latter comprise 139 aggravated-assault, 118 rape and 68 robbery records, with zero murder-category records in this APD footprint. That zero is scoped to this feed and geography. Another 808 records carry the selected non-aggravated assault codes, and 316 carry harassment/stalking codes. The remaining record cannot be waved away as unimportant.

Location also changes interpretation. Of the 325 serious-category records, 149 are classified at a residence/home and 85 at a street, road, alley or sidewalk. During 2020–2024, residences and parking facilities together account for 2,461 of 3,208 property reports, or 76.7%. A count drawn around an apartment includes events with very different relationships to a student walking past it.

## Street blocks: concentration, then a test on later years

The public street services cover a shorter recent period than the ten-year incident table. After the timestamp audit described below, a conservative linkage recovers recorded occurrence dates from the incident table. Extending the map download through the current 2026 snapshot recovers 258 late-filed reports about 2022–2025 occurrences, producing 40,065 linked records across the broad study envelopes. The exact West Campus target contains 2,181 property reports, 77 reports in the three mapped serious categories, and four arson reports. This is a matched subset, not a complete occurrence census. Public points describe hundred-address blocks; they cannot identify which building experienced an event. Rape and various other categories are absent from the mapped selection. [S1, S3, S4, S30]

![Figure 4: A geographic map places proportional circles at 141 published masked West Campus street-block coordinates, representing 2,162 linked property reports with recorded occurrences in 2022–2025. The study target is outlined; these locations do not identify buildings.](/research/deep-research/figures/crime-figure-4-masked-blocks.svg)

Figure 4. Recent property reports inside the exact West Campus target. Published point locations are aggregated to named hundred-address blocks; circle area represents the raw count. The 141 mapped blocks account for 2,162 of the 2,181 matched property reports. Another 19 lack a usable block and remain in the neighborhood denominator. This is a raw-count map, with no safety grades or building attribution.

| Block selected in 2022–2023 | 2022 | 2023 | 2024 | 2025 |
| :---- | :---- | :---- | :---- | :---- |
| 2100 RIO GRANDE ST | 23 | 15 | 16 | 19 |
| 700 23RD ST | 26 | 11 | 10 | 15 |
| 2500 LEON ST | 14 | 20 | 21 | 9 |
| 2400 SAN GABRIEL ST | 23 | 10 | 11 | 12 |
| 2200 RIO GRANDE ST | 11 | 21 | 25 | 16 |
| 2400 LEON ST | 12 | 13 | 12 | 9 |
| 2800 RIO GRANDE ST | 15 | 10 | 12 | 12 |
| 500 22ND ST | 11 | 14 | 4 | 5 |
| 2500 LONGVIEW ST | 8 | 16 | 6 | 6 |
| 900 26TH ST | 10 | 14 | 14 | 16 |

These ten blocks were selected using only the first two occurrence years in the matched subset, with a deterministic alphabetical tie break. They contain 297 of 1,018 property reports in that training period (29.2%), then 131 of 584 in 2024 (22.4%) and 119 of 579 in 2025 (20.6%). The combined later share is 250 of 1,163 (21.5%). This provides a more useful check of persistence than selecting the busiest places after seeing all four years.

Selecting the top ten using all four years yields 591 of 2,181 linked reports (27.1%); the top twenty contain 43.9%. There is concentration, but those results reject the proposed claim that a few blocks account for most property reports, at least when “few” means ten or twenty published blocks in the matched subset. The unlinked map-date sensitivity gives almost the same later share, 21.4%. These results caution against treating a ranking as a permanent characteristic. Crime-concentration research already warns that sparse events and the number of places can create mechanical concentration. This study lacks a complete inventory of zero-report street blocks and does not claim a percentage of all streets or an exposure-adjusted causal hotspot. [S17]

The matched map has 19 property records without a usable block number. They remain in the neighborhood denominator and are excluded from block rankings. In the full unlinked map-date window, a 25-meter inward or outward shift changes the property count from 2,261 to 2,164 or 2,302; the three mapped serious categories change from 82 to 74 or 92. Boundary streets matter; the public point is not a surveyed building location. The full map-window West Campus property match rate is 96.4%; unresolved cases are retained in the audit rather than assigned invented occurrence times.

## The hour problem: two different sources of false precision

First, the map clock appears to describe reporting. The initial 42,253 selected records can be linked conservatively to 40,023 incident-table reports by matching offense code, reported local date and minute, and the official census block group containing the public point, then rejecting one-to-many and many-to-one matches. Of those linked records, 31,489 (78.7%) have an occurrence date/time different from the map’s fields labeled occurrence. Some differences cross years: an apparent January 2022 map event matches a December 2021 occurrence reported in January. The raw fields and all unresolved cases are retained. [S1, S3, S4]

This is an empirical linkage, not an official shared-ID crosswalk. Coincidental matches remain possible; the checks make the diagnostic persuasive without giving it the authority of an agency-certified join. A city explanation or a direct event-ID crosswalk could change the interpretation. The official human-readable legacy field aliases also say “Occurrence Date” and “Occurrence Time,” so the problem cannot be resolved by simply reading a different label.

Within the same 2,181 linked West Campus property reports, the source map places eight in the 1 a.m. hour; the incident table’s occurrence field places 98 there. During 9 a.m.–4:59 p.m., the source map places 1,347 reports, compared with 726 by recorded occurrence. This comparison holds the reports and geography constant. The clock alone changes the pattern. Two West Campus linked records have same-day occurrence clocks later than their report clocks; they are flagged for sensitivity rather than quietly corrected.

![Figure 5: Paired bars compare two verified windows among the same 2,181 linked West Campus property reports. The map clock places 8 reports in the 1 a.m. hour versus 98 by incident occurrence; for 9 a.m.–4:59 p.m., the counts are 1,347 versus 726.](/research/deep-research/figures/crime-figure-5-two-clocks.svg)

Figure 5. Two verified windows from the same 2,181 linked West Campus property reports in 2022–2025, grouped using the map's occurrence-labeled fields and the incident table's occurrence field. The 1 a.m. window spans one hour; 9 a.m.–4:59 p.m. spans eight. Each panel has its own count scale. A full paired 24-hour series was not available in the supplied workbook and is not reconstructed here. Occurrence time remains subject to rounding and interval uncertainty.

The audit found a separate classification defect in the newer public GIS service: its layer labeled aggravated assault returned robbery codes and duplicate robbery records. The city-linked older service’s corresponding layer contains genuine aggravated assaults, and that verified layer is used here. This finding concerns the public service; it does not establish that the currently linked consumer map displays the wrong layer. Computer-security and fiduciary-property exceptions were also removed from the newer Theft layer before physical property analysis.

![Figure 6: Percentage bars show occurrence-time rounding in the 2016–2025 West Campus property record: 3,171 of 6,056 reports fall exactly on an hour, including 452 of the 618 reports in the midnight hour and 321 of the 476 reports in the noon hour.](/research/deep-research/figures/crime-figure-6-time-quality.svg)

Figure 6. The incident table’s own occurrence clock has a different limitation: substantial rounding. Each bar uses its own stated denominator: all 6,056 property reports, the 618 in the midnight hour, or the 476 in the noon hour. Rust shows exactly rounded timestamps; the open segment shows other minutes. Midnight and noon are subsets of the all-hours bar. This diagnostic does not recover a corrected event-time distribution.

Second, even the incident table’s occurrence clock is not necessarily precise. In West Campus’s ten-year property record, 3,171 of 6,056 timestamps (52.4%) fall exactly on the hour. The midnight hour contains 618 reports, 452 of them at exactly 00:00. Noon has 476 reports, 321 exactly at 12:00. Removing round-hour records changes the apparent hourly pattern, but it also removes potentially valid observations, so it is presented only as a sensitivity. Another 2,690 property reports (44.4%) were filed more than one calendar day after their recorded occurrence date.

Unattended-property crimes may be known only to have happened within an interval. Research with independently timed thefts shows why using one endpoint can distort temporal analysis. The Austin extract does not supply a genuine occurrence-from/occurrence-to interval, so this study does not invent one using report time or redistribute midnight records arbitrarily. [S16]

The serious-category data are too sparse to rescue a precise corner-hour ranking. Across West Campus’s 12 selected block groups and 24 hours, 259 of 288 cells (90%) have zero or one serious-category report during 2020–2024; the largest has four. Over the full ten years, the largest cell has six. At still finer street-block resolution there is less information per cell. An empty cell means no selected report in this extract, not evidence that the next walk is safe.

## What lighting and building security can support

The companion lighting layer contains 62,322 unique Austin 311 requests created during 2016–2025 across the selected street-light categories. It preserves duplicate, administrative, mass-entry and missing-location flags. About 4.94% lack coordinates. Category names changed around 2021–2022. A case’s creation and closure are administrative dates: they do not establish when a light went dark or when illumination returned. Multiple requests can concern the same fault. [S22]

Within the exact study polygons, West Campus has 539 lighting requests, including 499 in the maintenance-primary subset after the stated exclusions. North University has 239, Hyde Park 371, the Riverside study area 946 and the East study area 570 total requests. These counts share the street-map study boundaries; the resident-rate footprints are different. They are reports of lighting issues, not measured outages or evidence of a crime-prevention effect.

A simple correlation between complaints and crime would have an ambiguous direction. More residents may produce both reports and service requests; an already troubled block may receive priority for a lighting project. Austin’s January 2022 update describes prioritization that includes lighting deficiencies and then crime, crashes and community concerns. That selection process prevents treating completed projects as randomly assigned. A useful effect study needs dated pole-level interventions, verified outage/restoration periods, comparable untreated locations and checks for prior trends. [S23]

The building-security question is currently unresolved. First-party apartment pages advertise gates, access controls, locks and package storage. Those claims establish advertised features, not installation dates, functioning access controls or effectiveness. The stated collection of 161 geolocated buildings, resident accounts and complaint cases could not be located in the connected material available for this research. No building comparison or causal security effect has been fabricated. [S27, S28]

When that file is supplied, the safe initial join is block context around a building, with an explicit spatial resolution label. A masked report should never be attached to the nearest apartment as though it occurred there. A stronger evaluation would use verified building-specific incidents, occupied beds, parking supply, package volume where available, feature installation dates and documented outages. Security investment can respond to prior crime, and larger buildings create more targets and more opportunities to report; a feature-versus-no-feature comparison would otherwise be confounded.

## Campus records and the practical journey

Clery is useful but has a different scope. The 2026 university report contains 2023–2025 statistics and distinguishes on-campus, student-housing, noncampus and public-property categories. It draws on multiple reporting channels. It is not a census of all West Campus, and its totals cannot simply be added to APD. UTPD’s daily log and dashboards add important context, but calls, reports, offenses and institutional disclosures have different units. A shared event identifier or documented cross-agency reconciliation is required before creating a combined total. [S20, S21]

For a student deciding how to get home at 1 a.m., service eligibility may be more actionable than an unstable cell ranking. Sure Walk is a campus-origin service; starting at a West Campus apartment is a different trip. UT Night Rides currently operates from campus to eligible home destinations between 11 p.m. and 4 a.m., subject to its program rules. West Campus Ambassadors offers escorts inside its service zone, including neighborhood-origin trips. The official program pages should be checked for current hours, eligibility and coverage. “Longhorn Lights” refers to a holiday display; it should not be substituted for the city’s permanent lighting program. [S24–S26, S31]

This research supports inspecting the route, entry, parking and package arrangements separately. It does not establish a universally safest block or hour, and it does not justify discounting harassment or sexual harm because a public map is sparse. A route-specific exposure estimate would require pedestrian counts, trip timing and a more complete harm record than these feeds provide.

## How sure are these findings?

| Finding | Assessment | What would change it |
| :---- | :---- | :---- |
| West property rate above Austin; selected serious rate below | High confidence as a comparison of this APD record; robust across tested West definitions. | Material source revisions, a mismatched denominator, or a combined agency series with a different pattern. |
| North Campus property ranking | Definition-dependent. | An agreed footprint and matched population/exposure denominator. |
| West map density versus Riverside resident rate reverses | High confidence in the arithmetic; causal explanation unproven. | A different exposure measure or materially different geography. |
| Public map clock largely matches report time | Strong empirical evidence with conservative linkage; agency confirmation outstanding. | An official crosswalk or documented semantics explaining the observed matches differently. |
| Ten past hotspot blocks dominate later reports | Rejected as a majority claim; later linked share 21.5%. | A different prespecified spatial unit or independently validated exposure-adjusted model. |
| Towers, lights or advertised security caused a safety change | Unresolved. | Historical exposure, intervention dates, attribution and a credible comparison design. |

No generic confidence band can absorb underreporting, agency substitution, a mistaken timestamp meaning or a poor geographic proxy. This is why the report emphasizes exact retrieved counts, population margins of error, boundary sensitivities, missingness, held-out periods and explicit evidence grades. It preserves disagreement rather than averaging incompatible sources into one score.

# Source ledger

S1. Austin Police Department, Crime Reports. [https://data.austintexas.gov/Public-Safety/Crime-Reports/fdj4-gpfu](https://data.austintexas.gov/Public-Safety/Crime-Reports/fdj4-gpfu) — Incident table and live API metadata; highest offense per report; retrieved November 1–2, 2026.

S2. City of Austin, View Crime Statistics. [https://www.austintexas.gov/services/view-crime-statistics](https://www.austintexas.gov/services/view-crime-statistics) — Official scope, updates, unfounded records and comparison cautions.

S3. City-linked CrimeViewer service. [https://maps.austintexas.gov/gis/rest/APDCrimeViewer/APD\_Reported\_Crimes/MapServer](https://maps.austintexas.gov/gis/rest/APDCrimeViewer/APD_Reported_Crimes/MapServer) — Published block locations; genuine aggravated-assault layer used.

S4. Newer public city GIS service. [https://maps.austintexas.gov/arcgis/rest/services/CrimeViewer\_new/APD\_Reported\_Crimes\_new/MapServer](https://maps.austintexas.gov/arcgis/rest/services/CrimeViewer_new/APD_Reported_Crimes_new/MapServer) — Selected verified layers; duplicated/mislabeled layer 2 excluded.

S5. APD census block groups. [https://data.austintexas.gov/d/dwa9-qvcr](https://data.austintexas.gov/d/dwa9-qvcr) — Official polygons and identifiers used to align incidents and population.

S6. City of Austin neighborhood planning areas. [https://maps.austintexas.gov/gis/rest/Shared/Zoning\_2/MapServer/20](https://maps.austintexas.gov/gis/rest/Shared/Zoning_2/MapServer/20) — Official target polygons; exact object IDs preserved in GeoJSON.

S7. U.S. Census Bureau, 2024 ACS five-year summary files. [https://www2.census.gov/programs-surveys/acs/summary\_file/2024/table-based-SF/data/5YRData/](https://www2.census.gov/programs-surveys/acs/summary_file/2024/table-based-SF/data/5YRData/) — B01003 population and margins of error; B25001 housing units. Period 2020–2024.

S8. U.S. Census Bureau, ACS summary file documentation. [https://www.census.gov/programs-surveys/acs/data/summary-file.html](https://www.census.gov/programs-surveys/acs/data/summary-file.html) — Period estimates and table-based file documentation.

S9. City of Austin, May 6, 2004 council agenda. [https://www.austintexas.gov/content/may-6-2004-austin-city-council-regular-meeting](https://www.austintexas.gov/content/may-6-2004-austin-city-council-regular-meeting) — Item Z004 distinguishes Heritage, Shoal Crest and West University.

S10. The Texas Tribune, Urban Woes Regularly Spill Onto UT Campus, April 19, 2016. [https://www.texastribune.org/2016/04/19/urban-woes-spill-ut-austin-campus/](https://www.texastribune.org/2016/04/19/urban-woes-spill-ut-austin-campus/) — Prior map of 165 selected UTPD non-affiliate incidents; coverage cautions.

S11. The Daily Texan, Amid crime, safety concerns, West Campus community members determine a path forward, April 15, 2024. [https://thedailytexan.com/2024/04/15/amid-crime-safety-concerns-west-campus-community-members-determine-a-path-forward/](https://thedailytexan.com/2024/04/15/amid-crime-safety-concerns-west-campus-community-members-determine-a-path-forward/) — Existing reporting on student experience, property crime and lighting.

S12. DoorProfit, West Campus crime page. [https://www.doorprofit.com/crime-statistics/city/Austin-TX/neighborhood/west\_campus/](https://www.doorprofit.com/crime-statistics/city/Austin-TX/neighborhood/west_campus/) — Sampled commercial answer; internal inconsistencies as retrieved, not an independent crime source.

S13. Austin Crime Report, West Campus. [https://www.austincrimes.com/neighborhoods/west-campus/](https://www.austincrimes.com/neighborhoods/west-campus/) — Existing neighborhood mapping and grades; counts not reused.

S14. r/UTAustin, walking home alone question. [https://www.reddit.com/r/UTAustin/comments/mk5z0u/how\_safe\_are\_the\_areas\_in\_west\_campus\_where\_all/](https://www.reddit.com/r/UTAustin/comments/mk5z0u/how_safe_are_the_areas_in_west_campus_where_all/) — Illustrative self-selected discussion; no representative fear estimate.

S15. r/UTAustin, safe places to park a car. [https://www.reddit.com/r/UTAustin/comments/1teey7p/what\_are\_safe\_places\_in\_west\_campus\_to\_park\_a\_car/](https://www.reddit.com/r/UTAustin/comments/1teey7p/what_are_safe_places_in_west_campus_to_park_a_car/) — Illustrative evidence that property protection also concerns students.

S16. Ashby and Bowers, A comparison of methods for temporal analysis of aoristic crime, 2013. [https://link.springer.com/article/10.1186/2193-7680-2-1](https://link.springer.com/article/10.1186/2193-7680-2-1) — Primary research on uncertain occurrence intervals; not an Austin validation.

S17. Chalfin, Kaplan and Cuellar, Re-Examining the Law of Crime Concentration. [https://crim.sas.upenn.edu/node/1935](https://crim.sas.upenn.edu/node/1935) — Primary research motivating zero-street inventories and future-period tests.

S18. UT News, UTPD increases West Campus patrol, August 26, 2025. [https://news.utexas.edu/2025/08/26/utpd-increases-west-campus-patrol-cross-trains-with-apd-to-enhance-safety/](https://news.utexas.edu/2025/08/26/utpd-increases-west-campus-patrol-cross-trains-with-apd-to-enhance-safety/) — Dedicated district effective August 4, 2025; patrol boundary expansion.

S19. UTPD, Emergency call service unaffected by city change. [https://police.utexas.edu/news/utpd-emergency-call-service-unaffected-city-austin-change](https://police.utexas.edu/news/utpd-emergency-call-service-unaffected-city-austin-change) — October 1, 2021 APD reporting/response change and UTPD distinction.

S20. UT Austin, 2026 Annual Security and Fire Safety Report. [https://compliance.utexas.edu/sites/default/files/documents/ASFSR%202026\_0.pdf](https://compliance.utexas.edu/sites/default/files/documents/ASFSR%202026_0.pdf) — 2023–2025 Clery statistics; institutional geography and reporting channels.

S21. UTPD interactive transparency dashboards. [https://police.utexas.edu/records-reports/interactive-transparency-dashboards](https://police.utexas.edu/records-reports/interactive-transparency-dashboards) — Dashboard coverage, calls versus crimes and institutional reporting context.

S22. Austin 311 public data. [https://data.austintexas.gov/Utilities-and-City-Services/Austin-311-Public-Data/xwdj-i9he](https://data.austintexas.gov/Utilities-and-City-Services/Austin-311-Public-Data/xwdj-i9he) — 62,322 selected lighting requests created 2016–2025; dates are administrative events.

S23. Austin Energy West Campus lighting update, January 27, 2022. [https://services.austintexas.gov/edims/document.cfm?id=375536](https://services.austintexas.gov/edims/document.cfm?id=375536) — Installation progress and prioritization criteria; crime helped select interventions.

S24. UT Austin, Sure Walk. [https://parking.utexas.edu/transportation/walking](https://parking.utexas.edu/transportation/walking) — Campus-origin escort program; consult current hours and pickup eligibility.

S25. UT Austin, UT Night Rides. [https://parking.utexas.edu/transportation/ut-night-rides](https://parking.utexas.edu/transportation/ut-night-rides) — Campus-origin eligible rides home; current 11 p.m.–4 a.m. service window.

S26. West Campus Ambassadors FAQ. [https://wcambassadors.org/faq/](https://wcambassadors.org/faq/) — Neighborhood-zone safety escorts, contact and operating hours.

S27. Regents West at 26th amenities. [https://www.regentswest26.com/amenities](https://www.regentswest26.com/amenities) — First-party example of advertised controlled access; not effectiveness evidence.

S28. 21 Pearl amenities. [https://www.21pearlst.com/amenities/](https://www.21pearlst.com/amenities/) — First-party example of access controls and package storage; not historical uptime.

S29. U.S. Census Bureau, 2025 TIGER/Line roads. [https://www2.census.gov/geo/tiger/TIGER2025/ROADS/tl\_2025\_48453\_roads.zip](https://www2.census.gov/geo/tiger/TIGER2025/ROADS/tl_2025_48453_roads.zip) — Travis County street geometry used only as a basemap.

S30. APD Crime Search Guide. [https://data.austintexas.gov/stories/s/6vpz-c8m4](https://data.austintexas.gov/stories/s/6vpz-c8m4) — Public mapping guidance and location-publication limitations.

S31. UT Austin, Longhorn Lights. [https://www.utexas.edu/longhornlights](https://www.utexas.edu/longhornlights) — Official description of the holiday display; distinct from permanent safety lighting.


## Supporting data downloads

The public package contains curated, dated aggregate snapshots, dataset definitions and source notes. Its Excel workbook contains values, rather than the original editable formulas. The source and formula notes describe the reproducible scope.

- [Curated data, definitions and source notes (ZIP)](/research/deep-research/data/west-campus-crime-and-safety-support.zip)
- [Curated tables, values only (Excel)](/research/deep-research/data/west-campus-crime-and-safety/support.xlsx)
- [Primary comparison table (CSV)](/research/deep-research/data/west-campus-crime-and-safety/neighborhoods.csv)
- [Dataset definitions (JSON)](/research/deep-research/data/west-campus-crime-and-safety/definitions.json)