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cyrusobrien
Public
Edited
Jul 2, 2024
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petty_theft_input_comparison_data.sort((a, b) => a.close - b.close).slice(0, 1)
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estimate_drug_data = tidy(
drug_arrests,
mutate({
estimate: (d) =>
d.year > 2014 ? d.misd_drug_offenses : d.total_drug * 0.85,
close: (d) => Math.abs(d.estimate - arrests)
})
)
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number_impacted = arrests * pct_affected * pct_in_system
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cost_of_intervention_programs = marginal_cost_of_treatment * number_impacted
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number_receiving_custodial_sentence = number_impacted * failure_rate
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county_cost_of_jail_pretrial = number_impacted * alos_jail * marginal_cost_jail
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state_cost_of_prison_program_failure = number_receiving_custodial_sentence *
fail_to_prison_rate *
marginal_cost_prison
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county_cost_of_jail_program_failure = number_receiving_custodial_sentence *
(1 - fail_to_prison_rate) *
marginal_cost_jail *
365
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county_costs_tmf = county_cost_of_jail_pretrial +
county_cost_of_jail_program_failure
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total_costs_tmf = county_costs_tmf + state_cost_of_prison_program_failure
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table1 = tidy(
drug_arrests,
(items) => items.filter((d) => d.year == 2019),
select(["narcotics", "dangerous_drugs", "other_felony_drug"]),
pivotLonger({
cols: ["narcotics", "dangerous_drugs", "other_felony_drug"],
namesTo: "type",
valuesTo: "arrests"
}),
mutate({
"fraction containing fentanyl": (d) =>
d.type == "narcotics"
? fentanyl_contam_narcotics
: d.type == "dangerous_drugs"
? fentanyl_contam_dd
: fentanyl_contam_other,
"felony fentanyl arrests": (d) =>
Math.round(d.arrests * d["fraction containing fentanyl"])
})
)
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total_drug_arrests_for_chart = tidy(
drug_arrests,
mutate({
close: (d) => Math.abs(d.total_drug - total_drug_arrests)
})
)
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number_of_arrests_fentanyl = Object.values(
tidy(table1, summarize({ total: sum("felony fentanyl arrests") }))[0]
)[0]
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number_of_people_fentanyl = number_of_arrests_fentanyl * 0.9
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number_of_people_affected_annually_fentanyl_enhancement = number_of_people_fentanyl * more_than_28g +
number_of_people_fentanyl * more_than_100g +
number_of_people_fentanyl * more_than_500g
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increase_in_prison_population = number_of_people_fentanyl * more_than_28g * 3 +
number_of_people_fentanyl * more_than_100g * 5 +
number_of_people_fentanyl * more_than_500g * 5
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prison_costs_due_to_fentanyl = (increase_in_prison_population *
marginal_cost_prison) /
2
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fentanyl_arrests_table = Inputs.table(table2)
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table2 = tidy(
drug_arrests,
(items) => items.filter((d) => d.year == 2012),
select([
"narcotics",
"dangerous_drugs",
"other_felony_drug",
"total_drug",
"marijuana"
]),
mutate({
narcotics: (d) => d.narcotics / d.total_drug,
dangerous_drugs: (d) => d.dangerous_drugs / d.total_drug,
other_felony_drug: (d) => (d.other_felony_drug + d.marijuana) / d.total_drug
}),
pivotLonger({
cols: ["narcotics", "dangerous_drugs", "other_felony_drug"],
namesTo: "type",
valuesTo: "fraction of drug arrests"
}),
select(["type", "fraction of drug arrests"]),
mutate({
"fraction containing fentanyl": (d) =>
d.type == "narcotics"
? fentanyl_contam_narcotics
: d.type == "dangerous_drugs"
? fentanyl_contam_dd
: fentanyl_contam_other,
"fentanyl arrests": (d) =>
Math.round(
total_drug_arrests *
d["fraction containing fentanyl"] *
d["fraction of drug arrests"]
)
})
)
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number_of_total_arrests_fentanyl = Object.values(
tidy(table2, summarize({ total: sum("fentanyl arrests") }))[0]
)[0]
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armed_fentanyl_annual = number_of_total_arrests_fentanyl * fraction_armed
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armed_fentanyl_increase_in_prison_pop = armed_fentanyl_annual * 3
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state_costs_prison_armed_fentanyl = armed_fentanyl_annual * marginal_cost_prison
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petty_theft_input_comparison_data = tidy(
theft_arrests,
mutate({
close: (d) => Math.abs(d.petty_theft - misdemeanor_theft_arrests)
})
)
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annual_jail_admissions_pretrial = misdemeanor_theft_arrests * pct_2priors
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county_costs_pretrial_theft = annual_jail_admissions_pretrial *
alos_jail_theft *
marginal_cost_jail
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people_sentenced_to_jail = annual_jail_admissions_pretrial *
pct_misd_theft_in_system * pct_custodial_sentence *
(1 - pct_sentenced_to_prison)
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county_cost_jail_sentence = people_sentenced_to_jail * 365 * marginal_cost_jail
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people_sentenced_to_prison = annual_jail_admissions_pretrial *
pct_misd_theft_in_system *
pct_sentenced_to_prison *
pct_custodial_sentence
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state_cost_prison_petty_theft_2priors = people_sentenced_to_prison *
marginal_cost_prison
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state_costs = state_cost_of_prison_program_failure +
state_cost_prison_petty_theft_2priors +
state_costs_prison_armed_fentanyl +
prison_costs_due_to_fentanyl
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county_costs = county_cost_jail_sentence +
county_cost_of_jail_pretrial +
county_cost_of_jail_program_failure +
county_costs_pretrial_theft
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cost_of_intervention_programs
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county_cost_of_jail_pretrial
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estimated_total_cost = cost_of_intervention_programs + county_costs + state_costs
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total_increase_people_incarcerated = number_impacted *
failure_rate *
fail_to_prison_rate *
2 + // tmf prison sentence population
(1 - fail_to_prison_rate) * number_impacted * failure_rate + // tmf jail sentence population
(number_impacted * alos_jail) / 365 + // tmf jail pretrial population
increase_in_prison_population + // fentanyl sentencing enhancements prison population
armed_fentanyl_increase_in_prison_pop + // armed fentanyl sentence prison population
(annual_jail_admissions_pretrial * alos_jail_theft) / 365 + //theft pretrial population
people_sentenced_to_jail + // theft jail sentence population
people_sentenced_to_prison * 2 // theft prison sentence population
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sud_spending_data = FileAttachment(
"average outpatient service rate -- all counties@3.csv"
).csv({ typed: true })
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