ghasemy_2020_servant_leadership

2,694 responses from 449 respondents to 6 items.

One of 4 tables from the same source; this one measures Servant leadership (conceptual skills, behaving ethically). The others are listed under Related tables.

About this table

DescriptionPerceived servant leadership, conceptual skills (3) and behaving ethically (3), 6 items, 1-5; N = 449 academics with science backgrounds; cov_tenure.
ReferenceGhasemy, M. (2020). Replication Data for: servant leadership behaviors of academics with science backgrounds and their organizational outcomes (commitment, satisfaction, and motivation) [Data set]. Harvard Dataverse. https://doi.org/10.7910/DVN/2HFVF7
LicenceCC0 1.0
Source datahttps://doi.org/10.7910/DVN/2HFVF7

Size and shape

Responses2,694
Respondents449
Items6
Response categories5
Responses per respondent6
Responses per item449
Density1
LongitudinalFALSE

Classification

sampleTargeted/specific, Workplace
construct typeOpinion/attitude
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)eng
construct nameServant leadership (conceptual skills, behaving ethically)

Codebook

This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, ghasemy_2020_servant_leadership.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
Respondent covariates
cov_tenureCovariate C_Tenure

What item codes and covariate values stand for is in the codebook released with the source data.

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("ghasemy_2020_servant_leadership")
# Python
pip install irw

import irw
df = irw.fetch("ghasemy_2020_servant_leadership")

How to cite

@misc{https://doi.org/10.7910/dvn/2hfvf7,
  doi = {10.7910/DVN/2HFVF7},
  url = {https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/2HFVF7},
  author = {Ghasemy, Majid},
  keywords = {Arts and Humanities, Social Sciences, behaving ethically, conceptual skills, job satisfaction, work motivation, organizational commitment},
  title = {Replication Data for: servant leadership behaviors of academics with science backgrounds and their organizational outcomes (commitment, satisfaction, and motivation)},
  publisher = {Harvard Dataverse},
  year = {2020}
}

Version and provenance

IRW versionv584
Redivis datasetitem_response_warehouse_5 v8.5
Redivis dataset DOI10.57761/41xy-5k56
Manifest pin for this IRW versionv8.5
Metadata sourceirw_meta v44.0