NaileR (version 1.2.2)

local_food: Local food systems survey

Description

These data were collected after a Q-method-like survey on sustainable food systems. Participants had to rank how acceptable they found 45 statements about a sustainable food system; then, they were asked if they agreed with 14 other statements.

Usage

local_food

Format

A data frame with 573 rows (participants) and 63 columns (questions):

• columns 1-45 statements about food systems

• columns 46-59 opinions

• columns 60-63 personal information

Examples

if (FALSE) {
# Processing time is often longer than ten seconds
# because the function uses a large language model.

library(FactoMineR)
library(NaileR)
data(local_food)

res_mca_food <- MCA(local_food, quali.sup = 46:63,
ncp = 100, level.ventil = 0.05, graph = FALSE)
res_hcpc_food <- HCPC(res_mca_food, nb.clust = 3, graph = FALSE)
don_clust_food <- res_hcpc_food$data.clust

intro_food <- 'A study on sustainable food systems
was led on several French participants.
This study had 2 parts. In the first part,
participants had to rate how acceptable
"a food system that..." (e.g, "a food system that
only uses renewable energy") was to them.
In the second part, they had to say
if they agreed or disagreed with some statements.'
intro_food <- gsub('\n', ' ', intro_food) |>
stringr::str_squish()

req_food <- 'I will give you the answers from one group.
Please explain who the individuals of this group are,
what their beliefs are.
Then, give this group a new name,
and explain why you chose this name.
Do not use 1st person ("I", "my"...) in your answer.'
req_food <- gsub('\n', ' ', req_food) |>
stringr::str_squish()

res_food <- nail_catdes(don_clust_food, num.var = 64,
introduction = intro_food,
request = req_food,
isolate.groups = TRUE, drop.negative = TRUE)
res_food[[1]] |> cat()
}