Skip to contents

Create an audit trail from quallmer objects

qlm_trail.Rd

Creates a complete audit trail documenting your qualitative coding workflow. Following Lincoln and Guba's (1985) concept of the audit trail for establishing trustworthiness in qualitative research, this function captures the full decision history of your AI-assisted coding process.

Usage

qlm_trail(..., path = NULL)

Arguments

...

One or more quallmer objects (qlm_coded, qlm_comparison, or qlm_validation). When multiple objects are provided, they will be used to reconstruct the complete workflow chain.

path

Optional base path for saving the audit trail. When provided, creates {path}.rds (complete archive) and {path}.qmd (human-readable report). If NULL (default), the trail is only returned without saving.

Value

A qlm_trail object containing:

runs

List of run information with coded data, ordered from oldest to newest

complete

Logical indicating whether all parent references were resolved

Details

Lincoln and Guba (1985, pp. 319-320) describe six categories of audit trail materials for establishing trustworthiness in qualitative research. The quallmer package operationalizes these for LLM-assisted text analysis:

Raw data

Original texts stored in coded objects

Data reduction products

Coded results from each run

Data reconstruction products

Comparisons and validations

Process notes

Model parameters, timestamps, decision history

Materials relating to intentions

Function calls documenting intent

Instrument development information

Codebook with instructions and schema

When path is provided, the function creates:

  • {path}.rds: Complete trail object for R (reloadable with readRDS())

  • {path}.qmd: Quarto document with full audit trail documentation

References

Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic Inquiry. Sage.

See also

qlm_code(), qlm_replicate(), qlm_compare(), qlm_validate()

Examples

# Load example coded objects
examples <- readRDS(system.file("extdata", "example_objects.rds", package = "quallmer"))

# View audit trail from two coding runs
trail <- qlm_trail(
  examples$example_coded_sentiment,
  examples$example_coded_mini
)
print(trail)
#> # quallmer audit trail (2 runs)
#> 
#> 1. example_sentiment (original)
#>    2026-02-05 01:29 | openai/gpt-4.1
#>    Codebook: Sentiment analysis
#> 
#> 2. example_mini (parent: example_sentiment)
#>    2026-02-05 01:29 | openai/gpt-4.1-mini
#>    Codebook: Sentiment analysis

# \donttest{
# Save complete audit trail (creates .rds and .qmd files)
qlm_trail(
  examples$example_coded_sentiment,
  examples$example_coded_mini,
  path = tempfile("my_analysis")
)
#> ✔ Trail saved to /tmp/RtmpXX83o0/my_analysis193871347195.rds
#> ✔ Report saved to /tmp/RtmpXX83o0/my_analysis193871347195.qmd
#> ℹ Render with `quarto::quarto_render("/tmp/RtmpXX83o0/my_analysis193871347195.qmd")`
# }