germann_2026_redistribution

302,070 responses from 53,609 respondents to 4 items.

One of 5 tables from the same source; this one is the redistribution table. The others are listed under Related tables.

About this table

DescriptionLondon Bridge Attack 2017 panel survey; economic redistribution items (redistr1–redistr4); N≈53609; 1–5 Likert; wave=pre/during/post attack
ReferenceGermann, M., Godefroidt, A., & Mendez, F. (2026). Does Islamist Terrorism Still Affect Political Attitudes? European Journal of Political Research (forthcoming). Replication data: doi:10.7910/DVN/ALYGQS
DOI10.1017/S1475676526101017
LicenceCC0 1.0
Source datahttps://doi.org/10.7910/DVN/ALYGQS

Size and shape

Responses302,070
Respondents53,609
Items4
Response categories5
Responses per respondent5.635
Responses per item75517.500
Density1.409
LongitudinalTRUE

Classification

age rangeAdult (18+)
sampleInternet-based
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)ger

Item text

This table has item text in the IRW: the wording administered to respondents, not just the response codes.

InstrumentWhoGetsMyVoteUK 2017 voting advice application: economic redistribution policy statements
Mean words per item11.750
Mean characters per item76
Mean characters per response14.800
Flesch-Kincaid grade level9.078

Codebook

This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, germann_2026_terrorism.py. It is our best reading, not the source’s own codebook, and it may contain mistakes. Where the two disagree, the source data are the authority. If you find an error, please tell us.

ColumnWhat it isSource column
IRW standard columns
idIRW standard Identifier for the focal unit being measured — typically a person, but sometimes another entity (e.g., a word in a lexical task).made in the build script
itemIRW standard Item identifier.made in the build script
respIRW standard Response value.made in the build script
waveIRW standard Longitudinal wave indicator.not traced
Respondent covariates
cov_ageCovariate age
cov_eduCovariate edu
cov_genderCovariate gender
cov_lrCovariate lr
cov_pol_interestCovariate pol_interest
cov_regionCovariate region

What item codes and covariate values stand for is in the source’s codebook, Codebook (sheet in update-metaanalysis-data.xlsx).

Get the data

Download CSVno account neededBrowse on Redivisexplore and queryCroissant metadataHugging Face, Kaggle, OpenML

Or load it directly in R or Python (both need a free Redivis account; the first call opens a browser to sign in):

# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("germann_2026_redistribution")
# Python
pip install irw

import irw
df = irw.fetch("germann_2026_redistribution")

How to cite

@article{Germann_2026, title={Does Islamist terrorism still affect political attitudes?}, ISSN={1475-6765}, url={http://dx.doi.org/10.1017/S1475676526101017}, DOI={10.1017/s1475676526101017}, journal={European Journal of Political Research}, publisher={Cambridge University Press (CUP)}, author={Germann, Micha and Godefroidt, Amélie and Mendez, Fernando}, year={2026}, month=Apr, pages={1–21} }

Version and provenance

IRW versionv566
Redivis datasetitem_response_warehouse_2 v33.0
Redivis dataset DOI10.57761/6m04-m698
Manifest pin for this IRW versionv33.0
Metadata sourceirw_meta v43.0