finaltable.Rmd

---
title: "GDOC Program Recidivism/Staffing Requirements"
subtitle: "`r format(Sys.Date(), '%B %Y')`"
geometry: "left=1.5cm,right=1.5cm,top=0cm,bottom=1cm"
---
\setlength{\headsep}{-0.25cm}
\pagenumbering{gobble}
\vspace{-2.6truecm}

```{r pretable, echo=FALSE, message=FALSE, warning=FALSE}
library(charlatan)
library(lubridate)
library(tidyverse)
library(knitr)
library(ggrepel)

#data setup
source("data_setup.R")
source("re_report.R")
source("execute.R")
source("toggle.R")
```

This report includes the overall recidivism rates (release years `r date1`-`r date2`) for evidence-based programming provided in the Gotham Department of Corrections facilities for high-risk people. Staffing numbers describe how many full-time employees are needed over the course of a year to keep each program running. Each program facilitator completes extensive training and must complete eight hours of continuing education each year. 

\small

```{r table, echo=FALSE, message=FALSE, warning=FALSE}
#programs to remove per the CWC report
source("rm_pgms.R")

#deduplicate across all columns
source("dedup.R")

#clean program names
source("roster_clean.R")

##create dataset of numerators and denominators
#recidivism rates overall
source("rates.R")

#clean program names
source("staff_clean.R")

#create table dataset
source("tabledata.R")

source("finaltable_report.R")
reportit |> rename(`Program (Graduated 2017-2018)`          = "program_official",
                   `Recidivism Rate (2018-2019)` = "recid_rate_all",
                   Staffing          = "num_staff") |> 
  kable()
```

\vspace{-0.5truecm}

```{r graphic, include=FALSE}
source2 <- function(file, start, end, ...) {
    file.lines <- scan(file, what=character(), skip=start-1, nlines=end-start+1, sep='\n')
    file.lines.collapsed <- paste(file.lines, collapse='\n')
    source(textConnection(file.lines.collapsed), ...)
}

#manage the data to produce recidivism rates
source("cwc_unw.R")

#manage the data to produce recidivism rates
#total clients served (all years, year1, year2)
source("cwc_w.R")

#build bar chart of recidivism rates across programs
source2("va_cs_webr.qmd",42,133)

#plot print
pdf(width=6.5,height=5,pointsize=15,file="rrfinal.pdf")
print(rrfinal)
dev.off()  

ggsave("rrfinal.png", width = 8, height = 6, units = "in")
```

\begin{figure}
\includegraphics{rrfinal.pdf}
\end{figure}

\normalsize

\vspace{-1truecm}

## Findings
\vspace{-0.4cm}
Overall, the program with the lowest recidivism rates is: `r reportit[which(reportit$recid_rate_all == min(reportit$recid_rate_all)),]$program_official`. The program with the highest recidivism rates is: `r reportit[which(reportit$recid_rate_all == max(reportit$recid_rate_all)),]$program_official`. The average weighted recidivism rate is `r w.a`.

\vspace{-0.3cm}

## Methodology
\vspace{-0.4cm}
All participants have taken one of these programs right before release. The cohort analyzed were released from prison in `r date1` and `r date2`. Overall recidivism rates are computed.