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Load the Ontario SIU director's-report corpus

Source: R/load_siu_reports.R
load_siu_reports.Rd

Returns the bundled Ontario Special Investigations Unit (SIU) director's-report table: one row per report drid, 65 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.

Usage

load_siu_reports(
  lang = c("all", "en", "fr"),
  as = c("data.frame", "tibble"),
  format = c("csv", "parquet")
)

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 rmorie SIU subsystem.

Arguments

lang

One of "all" (default), "en", or "fr": filter to the English-only, French-only, or all rows.

as

Return format: "data.frame" (default) or "tibble".

format

"csv" (the gzip CSV, default) or "parquet" (the same rows and columns, native codec).

Value

A data.frame (or tibble) of SIU director's-report rows.

Details

For every English report (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 100\ reports (witness-officer-only investigations are a genuine 0). French reports carry the parser values. See the siu pipeline repo for the audit provenance.

This is the machine-readable companion to the SIU parser and data-mining subsystem in rmorie / morie – the first open-source pipeline for the SIU director's-report corpus, created by Vansh Singh Ruhela as part of the MORIE / MRM framework. The table is regenerated from the parser over the full public corpus; see rmorie::morie_fetch_siu() to rebuild it live.

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 rmorie reads back. The same table is also in the typed data store: morie_data_load("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 <- load_siu_reports()
nrow(all)
#> [1] 5157
ncol(all)
#> [1] 65

# `lang` filters the corpus by report language.
en <- load_siu_reports(lang = "en") # English director's reports
fr <- load_siu_reports(lang = "fr") # French director's reports
nrow(en)
#> [1] 2182
nrow(fr)
#> [1] 2191

# `as = "tibble"` returns a tibble when the tibble package is present.
if (requireNamespace("tibble", quietly = TRUE)) {
  tb <- load_siu_reports(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 
#>                             467                             404 
#>            Peel Regional Police Niagara Regional Police Service 
#>                             188                              95 
#>         Hamilton Police Service 
#>                              91