---
title: "Equity Audit, Trajectory Analysis, and Corpus Chat"
output: rmarkdown::html_vignette
vignette: >
%\VignetteIndexEntry{Equity Audit, Trajectory Analysis, and Corpus Chat}
%\VignetteEngine{knitr::rmarkdown}
%\VignetteEncoding{UTF-8}
resource_files:
- figures/logo.svg
- figures/logo-dark.svg
---
[](https://github.com/CTTIR/scimapR/actions/workflows/R-CMD-check.yaml)
[](https://cttir.github.io/scimapR/)
[](https://CRAN.R-project.org/package=scimapR)
[](https://app.codecov.io/gh/CTTIR/scimapR?branch=main)
[](https://cran.r-project.org/package=scimapR)
[](https://cran.r-project.org/package=scimapR)
[](https://opensource.org/licenses/MIT)
[](https://lifecycle.r-lib.org/articles/stages.html#experimental)
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.width = 7,
fig.height = 5
)
```
## Equity and representation audit
scimapR includes built-in tools for auditing geographic, gender, funding,
and open-access representation -- with explicit confidence reporting and
limitation caveats.
```{r setup}
library(scimapR)
corpus <- sm_example_corpus(seed = 42)
```
### Geographic audit
```{r geo}
geo <- sm_audit_geographic(corpus)
head(geo)
```
### Open access audit
```{r oa}
oa <- sm_audit_oa(corpus)
head(oa)
```
### Equity dashboard
```{r dashboard, eval = requireNamespace("patchwork", quietly = TRUE), fig.width = 8, fig.height = 6, fig.cap = "Equity dashboard"}
sm_plot_equity_dashboard(corpus)
```
### Epistemic humility
All audit functions report confidence, method, and caveats. The print
methods include explicit limitation blocks. scimapR does not pretend
that automated inference is ground truth.
## Author trajectory analysis
scimapR can track an author's career evolution through topic pivots,
collaborator turnover, and productivity curves.
```{r trajectory}
# The example corpus includes a trajectory seed author
traj <- sm_author_trajectory(corpus, author_id = "A000000001")
print(traj)
```
```{r traj-plot, eval = requireNamespace("patchwork", quietly = TRUE), fig.width = 8, fig.height = 6, fig.cap = "Author trajectory"}
sm_plot_trajectory(traj)
```
## LLM-grounded corpus chat
scimapR can use an LLM to answer questions about a corpus, with every
claim anchored to actual works via retrieval-constrained citations.
```r
# Requires ellmer package
response <- sm_chat(
corpus,
"What methodological approaches dominate post-2020?",
provider = ellmer::chat_anthropic()
)
print(response)
```
The LLM only sees works that were actually retrieved. Citations are
constrained to those retrieved works -- no hallucinated references are
possible.
