“Panel (Portugal, Italy, France, Belgium, Slovenia)” & “Panel (Sweden, Norway)” → Panel
Eventuell überdenken wie sinnvoll diese Gruppierung ist - schmeißen wir hier nicht Äpfel mit Birnen zusammen?
“Panel (Portugal, Italy, France, Belgium, Slovenia)” & “Panel (Sweden, Norway)” → Panel
Eventuell überdenken wie sinnvoll diese Gruppierung ist - schmeißen wir hier nicht Äpfel mit Birnen zusammen?
“Germany (West)”, “Germany (East)”, “Germany (Baden-Württemberg)”, “Germany (Nordrhein-Westfalen)”, “Germany (Hessen)”, “Germany (Niedersachsen)”, “Germany (Hamburg)”, “Germany (Schleswig-Holstein)” & “Germany (Baden-Württemberg, Nordrhein-Westfalen, Hessen, Niedersachsen, Hamburg, Schleswig-Holstein)” → Germany
Eventuell unterteilen in BRD/DDR?
Vorschlag “State (Law)”, “State (Law), Tripartite Comission”, “State (Law), in discussion with employers and employees”, “Agreements between firms and the president”, “State (Law), agreement between trade unions and industry”, “State (Law) & collective agreements”, “State (Law), partly collective agreements” → State “Employers and unions (collective agreements)” & “Employers and unions (collective agreements) & plant-based (firm-based agreemenst)”, “Establishment” → Collective agreement “Establishment” → ?
WIr müssen diskutieren, ob Establishment
wirklich teil von Employers and employees
sein soll, oder ob wir das als eigenen Daummy kodieren und dafür Employers and employees
in Collective agreements
zurückbenennen.
df_clean$accompanying_measures
Ganz am Ende diskutieren
df_clean$wage_adjustment
Ganz am Ende diskutieren
df_clean$costs_overtime
Ganz am Ende diskutieren
Monthly
Es gibt nur 20 davon... wie damit umgehen?
df_clean$workers_working_hours
Eventuell für Unterscheidung Vollzeit/Teilzeit wichtig! Wie können wir das konzeptuell analysieren?
df_clean$econometric_issues_techniques
df_clean$workers_income
Evt. nutzbar? "Wer kann es sich leisten, AZV zu machen"?
df_clean$econometric_issues_techniques
df_clean$workers_income
Evt. nutzbar? "Wer kann es sich leisten, AZV zu machen"?
df_clean$workers_working_hours
Eventuell für Unterscheidung Vollzeit/Teilzeit wichtig! Wie können wir das konzeptuell analysieren?
Monthly
Es gibt nur 20 davon... wie damit umgehen?
df_clean$wage_adjustment
Ganz am Ende diskutieren
df_clean$costs_overtime
Ganz am Ende diskutieren
df_clean$accompanying_measures
Ganz am Ende diskutieren
Vorschlag “State (Law)”, “State (Law), Tripartite Comission”, “State (Law), in discussion with employers and employees”, “Agreements between firms and the president”, “State (Law), agreement between trade unions and industry”, “State (Law) & collective agreements”, “State (Law), partly collective agreements” → State “Employers and unions (collective agreements)” & “Employers and unions (collective agreements) & plant-based (firm-based agreemenst)”, “Establishment” → Collective agreement “Establishment” → ?
WIr müssen diskutieren, ob Establishment
wirklich teil von Employers and employees
sein soll, oder ob wir das als eigenen Daummy kodieren und dafür Employers and employees
in Collective agreements
zurückbenennen.
“Germany (West)”, “Germany (East)”, “Germany (Baden-Württemberg)”, “Germany (Nordrhein-Westfalen)”, “Germany (Hessen)”, “Germany (Niedersachsen)”, “Germany (Hamburg)”, “Germany (Schleswig-Holstein)” & “Germany (Baden-Württemberg, Nordrhein-Westfalen, Hessen, Niedersachsen, Hamburg, Schleswig-Holstein)” → Germany
Eventuell unterteilen in BRD/DDR?
“Panel (Portugal, Italy, France, Belgium, Slovenia)” & “Panel (Sweden, Norway)” → Panel
Eventuell überdenken wie sinnvoll diese Gruppierung ist - schmeißen wir hier nicht Äpfel mit Birnen zusammen?
Winter, T., Jose, P., Riordan, B., Bizumic, B., Ruffman, T., Hunter, J., Hartman, T. K., & Scarf, D. (2021). Left-wing support of authoritarian submission to protect against societal threat. PsyArXiv. https://doi.org/10.31234/osf.io/hu9ef
This is for a time picker. If you're picking times for today, you may pick a time that is 15 minutes from now. It's valid now because it's currently in the future. If you don't touch the form for the next 20 minutes then click submit, the submission should be prevented because your selected time is now 5 minutes in the past.
Daniël Lakens on Twitter. (n.d.). Twitter. Retrieved September 23, 2020, from https://twitter.com/lakens/status/1308115862247952386
Michael Eisen on Twitter: “A core problem in science publishing today is that we have a system where the complex, multidimensional assessment of the rigor, validity, utility, audience and impact of a work that emerges from peer review gets reduced to a single overvalued ‘accept/reject’ decision.” / Twitter. (n.d.). Twitter. Retrieved August 10, 2020, from https://twitter.com/mbeisen/status/1291752487448276992
Mis-allocated scrutiny. (2020, June 24). The 100% CI. http://www.the100.ci/2020/06/24/mis-allocated-scrutiny/
Health, T. L. G. (2020). Publishing in the time of COVID-19. The Lancet Global Health, 8(7), e860. https://doi.org/10.1016/S2214-109X(20)30260-6
Overview—British Journal of Health Psychology. (n.d.). Wiley Online Library. https://doi.org/10.1111/(ISSN)2044-8287
British Journal of Social Psychology. (n.d.). Wiley Online Library. https://doi.org/10.1111/(ISSN)2044-8309
Fast-Tracking COVID-19 Submissions. (n.d.). Association for Psychological Science - APS. Retrieved June 11, 2020, from https://www.psychologicalscience.org/publications/psychological_science/psci-covid-19
Science in the time of COVID-19. Nat Hum Behav 4, 327–328 (2020). https://doi.org/10.1038/s41562-020-0879-9
Call for Papers: COVID19-Pandemic. (n.d.). Https://Www.Apa.Org. Retrieved June 11, 2020, from https://www.apa.org/pubs/journals/amp/call-for-papers-covid19-pandemic
Journal of Computational Social Science. Springer. Retrieved June 10, 2020, from https://www.springer.com/journal/42001/updates/17993070
American Psychological Association. Interdivisional call for papers: Developing resilience in response to stress and trauma. Apa.org. https://www.apa.org/pubs/journals/hea/interdivisional-call-for-papers-resilience-stress-trauma
Chambers, C. (2020 March 16). CALLING ALL SCIENTISTS: Rapid evaluation of COVID19-related Registered Reports at Royal Society Open Science
10 Updates*
LISTSERV 16.0—SOCNET Archives. (n.d.). Retrieved April 20, 2020, from https://lists.ufl.edu/cgi-bin/wa?A2=ind2004&L=SOCNET&P=9667
Impact of staffing cap
The impact of staffing caps has been highlighted by numerous commentators and almost certainly plays a significant role in putting pressure on the planning workforce.
Staffing cap recommendation
That government review NDIA data to determine if there are staffing issues limiting the number of planners relative to the demand for plans. If this is the case, we argue that government should relax staffing caps.
Recommendation to lift staffing cap
The NDIA to lift the staffing cap to employ more NDIA planners and ensure NDIA planners are always used for participants with complex disabilities and/or lives. Where a LAC is the NDIA representative in a planning meeting, these LACs need to ensure they are trained and encouraged to work towards understanding individual needs and goals as opposed > to pre-empting needs based on disability type and therefore misrepresenting the actual needs of the participant.
Recommendation to increase staffing cap
Increased staffing cap to enable NDIA Delegates time to get Plans correct initially
How to post your data and materials
This blog post is very useful for people wanting to share their data or files anonymously. I just knew about this OSF feature by reading this post. Thank you Steve.