Create Custom Status Classification Rules

Helper function to create custom employment status classification rules for specific business contexts or analytical requirements. Supports flexible prior value mappings for different employment coding systems.

Usage

create_custom_status_rules(
  unemployment_threshold = 8,
  custom_labels = NULL,
  prior_labels = NULL,
  include_intensity = FALSE,
  include_transitions = FALSE
)

Arguments

unemployment_threshold

Days threshold for short vs long unemployment (default: 8)

custom_labels

Named list of custom status labels to override defaults

prior_labels

Named list mapping prior values to employment type labels. Keys should be string representations of prior values, values should be the corresponding employment type labels. Example: list("0" = "pt", "1" = "ft", "2" = "fixed", "5" = "intern")

include_intensity

Logical. Include employment intensity classifications

include_transitions

Logical. Include transition-based classifications

Value

List of custom classification rules compatible with classify_employment_status()

Details

**Key Features**:

1. **Custom Prior Labels**: Map any numeric prior values to meaningful labels. This enables support for industry-specific or organization-specific employment type coding systems.

2. **Flexible Thresholds**: Customize unemployment duration thresholds based on analytical requirements or policy definitions.

3. **Custom Label Systems**: Override default status labels to match organizational terminology or reporting requirements.

4. **Extension Support**: Include additional classification dimensions like employment intensity or transition-based classifications.

**Prior Labels Usage**: The prior_labels parameter is crucial for the enhanced flexible system. It maps string representations of prior values to employment type labels that will be used in the final status classifications.

Examples

# Basic custom rules with industry-specific employment types
healthcare_rules <- create_custom_status_rules(
  unemployment_threshold = 15,  # 15 days for healthcare sector
  prior_labels = list(
    "0" = "parttime",
    "1" = "fulltime",
    "2" = "locum",      # Temporary medical staff
    "3" = "agency",     # Agency workers
    "4" = "oncall"      # On-call staff
  )
)

# Advanced rules with custom labels and extended mappings
academic_rules <- create_custom_status_rules(
  unemployment_threshold = 90,  # Longer periods common in academia
  custom_labels = list(
    unemployed_short = "between_positions",
    unemployed_long = "career_transition"
  ),
  prior_labels = list(
    "1" = "tenured",
    "2" = "tenure_track",
    "3" = "adjunct",
    "4" = "postdoc",
    "5" = "visiting",
    "10" = "emeritus"
  ),
  include_intensity = TRUE
)

# Demonstrate the effect of custom prior labels
if (FALSE) { # \dontrun{
library(data.table)
segments <- data.table(
  cf = "PROF001",
  inizio = c(1, 30, 60),
  fine = c(29, 59, 90),
  arco = c(1, 0, 2),
  prior = c(2, NA, 4),  # tenure_track, unemployment, postdoc
  durata = c(29, 30, 31),
  over_id = c(1, 0, 2)
)

classified <- classify_employment_status(segments, academic_rules)
print(classified$stato)
# Expected: "occ_tenure_track", "between_positions", "occ_postdoc"
} # }

# Legacy system compatibility - mapping old codes to new labels
legacy_rules <- create_custom_status_rules(
  prior_labels = list(
    "100" = "manager",
    "200" = "supervisor",
    "300" = "specialist",
    "400" = "trainee",
    "999" = "consultant"
  )
)