Published: 26th January, 2021
It’s taken us a while to get our heads round what the University’s shaping for excellent redundancies plans might mean for NPB (Dept of Neuroscience, Psychology and Behaviour) because, well… let’s see…
We’ve had questions regarding (external consultant) DataHE’s projections of student recruitment figures throughout, but didn’t expect to be asking how on earth substantial projected EXPANSION of Neuroscience and Psychology teaching is to be achieved through redundancies???
Also, someone else might say it looks like they plan to eliminate entire research strands/groups based on their relationship to the buildings the University doesn’t want to reopen. We’re not saying this, because the pre-change engagement process lacked transparency entirely.
The 2 areas they want to concentrate research on – to deliver ‘bench to bedside’ that strengthens the ‘clinical interface’ – sound a bit similar to two existing research groupings (but not the same) and don’t appear to relate to several other existing areas at all.
So we again have serious questions about what the selection process has been in creating the at-risk of redundancy pool, of roles deemed redundant both to their research priorities and to expanding teaching programmes?
Are we to assume the University thinks staff in NPB are currently short on work to do? If so, they’re wrong. As a result of plans for redundancies in NPB in 2018 – and for those of you following all our threads, YES: THIS AGAIN. Put the plans through Turnitin please…
Staff lost through attrition over several years have not been replaced. Resulting staff shortages have already made workloads untenable BEFORE the pandemic started (does the University even remember a pandemic is happening to their staff & students??)
The pre-change engagement process reportedly drew on wildly inaccurate info about teaching loads and staffing numbers, so we’re on the edge of our seats waiting to find out if they’ve listened to staff feedback in this case, or ignored it and ploughed ahead with the wrong data.
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