In order for performance evaluation to rely solely on objective criteria, selection procedures must specifically address both conscious and unconscious biases based on non-academic factors. For individual academic performance to be comparable, it must be assessed according to uniform, transparent criteria that are both legally and scientifically permissible. In order to create a climate of trust and open discourse in research cooperation and performance assessment, one fundamental requirement is the acceptance of different individual life paths and gender equality.<\/p>\n\n\n\n
The factors mentioned in the General Equal Treatment Act (Allgemeines Gleichbehandlungsgesetz \u2013 AGG):<\/p>\n\n\n\n
may under no circumstances be included in an academic performance evaluation to the detriment of an individual since they are entirely irrelevant in this context.<\/p>\n\n\n\n
An individual\u2019s capacity to engage in academic activity may also be limited in time due to a certain personal situation. In particular, absences due to the individual\u2019s own serious illness or disability as well as absences due to family obligations (pregnancy, birth and care of children, care of relatives) are to be regarded as unavoidable. Generally speaking, researchers concerned are powerless to avoid such absences.<\/p>\n\n\n\n
With regard to a researcher\u2019s family planning, special note should be taken of the fact that<\/p>\n\n\n\n
The decision to become pregnant and\/or have children must not be counted as a disadvantage to female or male researchers at any point. Furthermore, it is important to consider that the decision to have children in a partnership places a significantly greater burden on the person bearing the child as compared to the non-bearing parent due to the factors of pregnancy, birth and, where applicable, breastfeeding.<\/p>\n\n\n\n
Providing long-term care for adult relatives can also be a time factor to be taken into consideration in performance evaluation.<\/p>\n\n\n\n
When allowing for individual circumstances, protection of the privacy of those concerned and the compliance with the relevant data protection law require a sensitive approach to personal data as well as any additional details of the individual\u2019s academic career and personal life. Systems must be in place to ensure data privacy, especially when it comes to handling highly sensitive data. What is more, voluntary provision of information and the confidentiality of the personal details must be guaranteed.<\/p>\n\n\n\n
The factors are relevant in the context of comparative individual performance evaluation so as to be able to relate academic performance to the time actually spent on academic activities. This includes adequately deducting disclosed periods of absence that were not the individual\u2019s own fault, e.g. as a result of family commitments, disability or chronic illness.<\/p>\n\n\n\n
In addition to the above-mentioned points on recognising periods of absence, there may be other ways in which disadvantages have to be compensated for in the performance evaluation (hardship provision). Cases of hardship apply where individuals suffer a major disadvantage that goes beyond the general risk to life and limb (to which everyone is subject) through no fault of their own. This is why it is important to incorporate appropriate hardship provisions when drawing up formal performance assessment procedures. To ensure equality of treatment, formal hardship provisions should provide for individual cases to be judged according to clear-cut, uniform criteria and for this to be documented accordingly.<\/p>\n\n\n\n
The academic evaluation of persons may only be based on their individual academic performance. In addition to avoiding legally prohibited discrimination, this also serves to ensure a purely qualitative selection.<\/p>\n","protected":false},"featured_media":0,"menu_order":0,"template":"","kommentar_cats":[257],"kommentar_tags":[182,188,252,191,224,184,214,179],"class_list":["post-5946","kommentare","type-kommentare","status-publish","hentry","kommentar_cats-general","kommentar_tags-bias-en","kommentar_tags-data-protection-data-privacy","kommentar_tags-diversity","kommentar_tags-documentation","kommentar_tags-early-career-researchers","kommentar_tags-equal-opportunities","kommentar_tags-performance-assessment","kommentar_tags-review-process"],"acf":[],"yoast_head":"\n