This statistic shows the share of employers that offer paid time off for volunteer work in the United States from 2015 to 2019. As of 2019, ** percent of employers in the U.S. offered paid time off for employees to do volunteer work.

Explanation/Overview:

Corresponding dataset for the analyses and results achieved in the CS Track project in the research line on participation analyses, which is also reported in the publication "Does Volunteer Engagement Pay Off? An Analysis of User Participation in Online Citizen Science Projects", a conference paper for the conference CollabTech 2022: Collaboration Technologies and Social Computing and published as part of the Lecture Notes in Computer Science book series (LNCS,volume 13632) here. The usernames have been anonymised.

Purpose:

The purpose of this dataset is to provide the basis to reproduce the results reported in the associated deliverable, and in the above-mentioned publication. As such, it does not represent raw data, but rather files that already include certain analysis steps (like calculated degrees or other SNA-related measures), ready for analysis, visualisation and interpretation with R.

Relatedness:

The data of the different projects was derived from the forums of 7 Zooniverse projects based on similar discussion board features. The projects are: 'Galaxy Zoo', 'Gravity Spy', 'Seabirdwatch', 'Snapshot Wisconsin', 'Wildwatch Kenya', 'Galaxy Nurseries', 'Penguin Watch'.

Content:

In this Zenodo entry, several files can be found. The structure is as follows (files and folders and descriptions).

corresponding_calculations.html

Quarto-notebook to view in browser

corresponding_calculations.qmd

Quarto-notebook to view in RStudio

assets

data

annotations

annotations.csv

List of annotations made per day for each of the analysed projects

comments

comments.csv

Total list of comments with several data fields (i.e., comment id, text, reply_user_id)

rolechanges

478_rolechanges.csv

List of roles per user to determine number of role changes

1104_rolechanges.csv

...

...

totalnetworkdata

Edges

478_edges.csv

Network data (edge set) for the given projects (without time slices)

1104_edges.csv

...

...

Nodes

478_nodes.csv

Network data (node set) for the given projects (without time slices)

1104_nodes.csv

...

...

trajectories

Network data (edge and node sets) for the given projects and all time slices (Q1 2016 - Q4 2021)

478

Edges

edges_4782016_q1.csv

edges_4782016_q2.csv

edges_4782016_q3.csv

edges_4782016_q4.csv

...

Nodes

nodes_4782016_q1.csv

nodes_4782016_q4.csv

nodes_4782016_q3.csv

nodes_4782016_q2.csv

...

1104

Edges

...

Nodes

...

...

scripts

datavizfuncs.R

script for the data visualisation functions, automatically executed from within corresponding_calculations.qmd

import.R

script for the import of data, automatically executed from within corresponding_calculations.qmd

corresponding_calculations_files

files for the html/qmd view in the browser/RStudio

Grouping:

The data is grouped according to given criteria (e.g., project_title or time). Accordingly, the respective files can be found in the data structure

In this table you will find annual figures on the number of volunteers aged 18 years or older, the average number of hours volunteers are active and the percentage of volunteers among the population aged 18 or older. The EBB asked whether respondents are volunteering and whether they do so for an organisation or institution. Those who answer both questions in the affirmative are considered to be an organised volunteer. Then it was asked for what type of organisation and for how many hours they are active. When someone does volunteering for multiple types of organisations, the total number of hours specified is distributed among those organisations. The data on volunteering comes from the Labour Force Survey (EBB). Data on the main source of income of respondents come from the Social Statistical File (SSB) and have been added to the EBB.

Data available for 2001-2009

Status of the figures Figures based on EBB are always final.

Amendment as of 7 December 2011: Data on main source of income have been included for reporting year 2009.

When are new figures coming? It’s about one-off data.

Corresponding dataset for the publication "Does Volunteer Engagement Pay Off? An Analysis of User Participation in Online Citizen Science Projects", a conference paper for the conference CollabTech 2022: Collaboration Technologies and Social Computing and published as part of the Lecture Notes in Computer Science book series (LNCS,volume 13632) here. Usernames have been anonymised.

The structure of the dataset is as follows:

Annotations

List of annotations made per day for each of the analysed projects.

annotations.csv

Comments

Total list of comments with several data fields (i.e., comment id, text, reply_user_id)

comments.csv

Rolechanges

List of roles per user to determine number of role changes

478_rolechanges.csv

1104_rolechanges.csv

...

Totalnetworkdata

Network data (edge and node sets) for the given projects (without time slices).

Edges

478_edges.csv

1104_edges.csv

Nodes

478_nodes.csv

1104_nodes.csv

Trajectories

Network data (edge and node sets) for the given projects and all time slices (Q1 2016 - Q4 2021)

478

Edges

edges_4782016_q1.csv

edges_4782016_q2.csv

edges_4782016_q3.csv

edges_4782016_q4.csv

...

Nodes

nodes_4782016_q1.csv

nodes_4782016_q4.csv

nodes_4782016_q3.csv

nodes_4782016_q2.csv

...

1104

Edges

...

Nodes

...

...

The Foreign Service Act of 1980 mandated a comprehensive revision to the operation of the Department of State and the personnel assigned to the US Foreign Service. As the statutory authority, the Foreign Affairs Manual (FAM), details the Department of Sta

BackgroundPsychosocial well-being, which assesses emotional, psychological, social, and collective well-being, could help measure risk and duration of sick leave in workers.ObjectiveThis study aims to build a structural equation model of a psychosocial well-being index based on 10 psychosocial factors and investigate its association with sick leave.MethodsData of workers using Wittyfit was collected in 2018. Psychosocial factors (job satisfaction, atmosphere, recognition, work-life balance, meaning, work organization, values, workload, autonomy, and stress) were self-assessed using health-related surveys, while sick leave records were provided by volunteer companies.ResultsA total of 1,399 workers were included in the study (mean age: 39.4 ± 9.4, mean seniority: 9.2 ± 7.7, 49.8% of women, 12.0% managers). The prevalence of absenteeism was 34.5%, with an average of 8.48 ± 28.7 days of sick leave per worker. Structural equation modeling facilitated computation of workers’ psychosocial well-being index (AIC: 123,016.2, BIC: 123,231.2, RMSEA: 0.03). All factors, except workload (p = 0.9), were influential, with meaning (β = 0.72, 95% CI 0.69–0.74), values (0.69, 0.67–0.70) and job satisfaction (0.64, 0.61–0.66) being the main drivers (p 

Family carers, central to sustainable care, are mostly of working age and employed full-time. Their rising numbers include many mobile workers. Incompatibility between family care and paid work is a known risk to sustainable care, but better evidence is needed of the support needed to promote wellbeing among working carers and those they support. This team’s research on Combining Work and Care: How do workplace support and technologies contribute to sustainable care arrangements is designed to inform policy and practice on the planning and resourcing of care by generating new insights into sustainable care and wellbeing through comparison of developments in the UK and other countries. Previous UK research on this topic has mostly focused on flexible working arrangements and organisational case studies. Little is known about how care leave (on which the UK has not legislated) might be introduced, or about the voluntary initiatives already being implemented by employers. This research focused on under-researched aspects of the support needed to sustain the wellbeing of ‘working carers’: measurement of impact; the role and potential of schemes designed to improve workplace support; the impact and characteristics of statutory care leave in other countries and of their voluntary, employer-led, equivalents in the UK. The main research questions were: 1. What support do working carers need to fulfill both their work and caring responsibilities? What are their highest priorities for such support? 2. What constitutes good workplace support for carers in employment? How does it enhance carers’ ability to integrate their paid employment and caring roles? 3. What is the impact of this support on carers, employers, care users and care workers? What are its costs and benefits for employers and for different types of employee? 4. What are the key features of established/emerging carer ‘workplace standard’, ‘employer recognition’ and ‘benchmarking’ schemes; what do they contribute to wellbeing and sustainability of care arrangements? 5. What are the characteristics, impact, uptake and outcomes of UK employers’ voluntary care leave schemes, and of statutory paid care leave schemes in other countries? 6. What aspects of worker and carer roles are amenable to improved co-ordination of care; in what ways and how can technology enhance the quality of care relationships, or produce wellbeing outcomes? 7. Which (if any) available technologies do working carers use, and how (if at all) do they assemble or modify these to provide the support they need? 8. Can technological innovations offer improved support for working carers reduce stress/overload or disconnection/ fragmentation in caring situations?