orm_priority: Compute risk priority scores and traffic light classification

In orisma: Occupational Risk Integrated Systematic Mapping and Analysis

Compute risk priority scores and traffic light classification

Description

orm_priority() assigns a priority level to each detected risk category using three criteria combined into a single priority score:

• Frequency (RCS): how saturated is this category in the literature

• Disconnection (WRDI): how far is the research from real worker data

• Evidence volume: number of records

Categories whose RCS exceeds context_rcs_threshold are flagged as context categories (the dominant topic of the corpus, not a risk per se) and are reported separately rather than mixed with risk categories.

Priority levels for non-context categories:

• RED: WRDI >= wrdi_high AND RCS >= 1. Over-studied technically but no worker data. Urgent preventive gap.

• AMBER: Moderate evidence OR partial worker data.

• GREEN: WRDI < wrdi_low. Good worker data connection.

• GREY: n_records < min_records. Insufficient evidence.

Usage

orm_priority(
  result,
  min_records = 2L,
  wrdi_high = 0.7,
  wrdi_low = 0.3,
  context_rcs_threshold = 15,
  lang = getOption("orisma.lang", "en")
)

Arguments

result	An orisma_result object.
min_records	Integer. Min records for evaluation. Default 2.
wrdi_high	Numeric. WRDI threshold for high disconnection. Default 0.7.
wrdi_low	Numeric. WRDI threshold for low disconnection. Default 0.3.
context_rcs_threshold	Numeric. RCS above which a category is considered a context category (dominant topic) rather than a risk. Default 15.
lang	Character. "en" or "es".

Value

A list with two data frames: ⁠$risks⁠ (priority-classified risk categories) and ⁠$context⁠ (dominant topic categories).

orisma documentation built on May 19, 2026, 1:07 a.m.