Returns the bundled Ontario Special Investigations Unit (SIU)
director's-report table: one row per report drid, 66 structured
columns (police service, incident / notification / decision dates,
investigator and witness / subject-official counts, affected-person
demographics, injuries, legislation, charges verdict, director's
decision, and news-release linkage), plus a panel_reviewed
flag.
Source
Ontario Special Investigations Unit director's reports, https://www.siu.on.ca/en/directors_reports.php (post-2018) and the Ontario Government archive (pre-2018). Parsed with the MORIE SIU parser.
Details
For the English reports marked panel_reviewed == "TRUE", the 16
key columns were verified by a multi-agent LLM review panel against
the full report text and the parser's guess resolved to the correct
value; the subject-official count is filled for every one of them
(witness-officer-only investigations are a genuine 0). A French report
carries its English report's reviewed case facts (the dates, the team,
the counts, the affected person's age and sex, the charges and the
director's view) and panel_reviewed == "FALSE"; its text fields
stay French, and its police_service is its English report's
service under the name the SIU's French pages use.
charges_recommended is "FALSE", "TRUE" or empty here
(every column is text); in the typed table,
mdload("siu_directors_reports"), it is logical
(FALSE, TRUE, or NA when the report does not say).
corrigenda holds the SIU's correction notice of a report (a
corrigendum is applied to the report it corrects, not counted as a
report). narrative_summary is the opening of the report's own
account of the incident (about 900 characters, at most 1,500, cut at a
sentence end): its "Incident Narrative" / "Description de l'incident"
section, or, in reports without one (2005-2016 and re-opened files), the
"Notification of the SIU" / "Avis a l'UES" section, which holds the
account there. It is empty on the 8 reports whose page has neither.
supplemental_materials lists the legislation and case-law links a
report cites.
police_service is the service of the subject officials – not the
force that notified the SIU, which is often a custody, requesting or
neighbouring service. Each correction to it is listed with the reason
read from the report in data-raw/siu_police_service_review.csv
of the source repository.
One row is one published report, keyed by drid and
_language. A case number can appear on more than one row: the SIU
publishes a further report when a case is reconsidered or reported again,
each with its own drid. Some schema columns (for example the raw
times of injury and notification, evidence types, and weapons used) are
not stated in the published reports and are empty throughout; they are
kept so the table's shape matches the parser's schema.
The table is the output of the SIU director's-report parser, the first
open-source pipeline for this corpus, created by Vansh Singh Ruhela as
part of the MORIE / MRM framework, regenerated over the full public
corpus. The parser itself is in the rmorie package
(rmorie::morie_fetch_siu() rebuilds the table live); nothing
here needs it.
This loader returns the corpus as text: every column is character and
an empty cell is "", which is the form the SIU parser writes and
reads back. The same table is also in the typed data
store: mdload("siu_directors_reports") applies the
bundled schema (integer drid and counts, NA for empty
cells), so counts of missing values differ between the two entry
points by construction; pick the typed store for analysis and this
loader for the parser round trip.
Examples
# Default: every parsed report, as a base data.frame.
all <- siuload()
nrow(all)
#> [1] 4613
ncol(all)
#> [1] 66
# `lang` filters the corpus by report language.
en <- siuload(lang = "en") # English director's reports
fr <- siuload(lang = "fr") # French director's reports
nrow(en)
#> [1] 2309
nrow(fr)
#> [1] 2304
# `as = "tibble"` returns a tibble when the tibble package is present.
if (requireNamespace("tibble", quietly = TRUE)) {
tb <- siuload(lang = "en", as = "tibble")
class(tb)
}
#> [1] "tbl_df" "tbl" "data.frame"
# The five police services with the most reports.
if (nrow(en)) {
top <- sort(table(en$police_service), decreasing = TRUE)
head(top, 5)
}
#>
#> Toronto Police Service Ontario Provincial Police
#> 503 450
#> Peel Regional Police Niagara Regional Police Service
#> 200 102
#> Ottawa Police Service
#> 99