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Record W3038114514 · doi:10.1136/vr.m2540

Don't waste this crisis

2020· article· en· W3038114514 on OpenAlexaboutno aff
Georgina Mills

Bibliographic record

VenueVeterinary Record · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCOVID-19 Pandemic Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsRecessionHospitalityShadow (psychology)Coronavirus disease 2019 (COVID-19)Government (linguistics)Falling (accident)Quarter (Canadian coin)BusinessPandemicPolitical scienceEconomic policyEconomic growthEconomicsGeographyMedicineLawPsychologyTourismEnvironmental health

Abstract

fetched live from OpenAlex

The UK is entering a new phase of the Covid-19 pandemic. Death rates and new cases are falling, and lockdown measures have begun to ease, so the economy can now start to recover. Last week, the government announced that the UK had moved to Covid-19 alert level three – the virus is considered to be ‘in general circulation’ but not rising. With shops opening and the hospitality sector gearing up to open next month, it feels like we are finally seeing light at the end of the tunnel. But just how long is the tunnel? The Organisation for Economic Co-operation and Development, which assesses economic progress and world trade, says the crisis will cast a long shadow over the world, triggering the ‘most severe recession in nearly a century’. The UK's economy is likely to fall by 11.5 per cent in 2020, a figure higher than other European countries, and if there is a second peak, the economy will fall further. We know from surveys carried out by the RCVS that practice turnover has taken a hit. Following the announcement of lockdown and the introduction of social distancing measures, April's survey found almost a quarter of practices reporting falls in their turnover of more than 75 per cent. Data from the latest survey in May indicate that as practices started to provide a more normal range of services, the number reporting this level of turnover loss had fallen to just 6 per cent. Preliminary results from the latest RCVS survey shows practices are starting to increase case loads, their turnover is improving and fewer staff are having to self isolate. But as we move to a new normal, albeit with social distancing measures still in place, what is in store for practices and their recovery? Could this be an opportunity? The profession needs to become more proactive Richard Casey, president of the Veterinary Management Group (VMG), says the profession now needs to become more proactive and start planning for the next 12 months. The VMG published a reemergence manual for the profession last month, which looked at the short-, medium- and long-term action that businesses can take. Instead of just concentrating on profit, it advised that practices use an approach that looks out for people too (the two being interrelated). This could take the form of extended practice opening hours to allow for more flexible working, with staff working longer but fewer days so that the same volume of work can be carried out. This could also have the advantage of offering appointment times that may be more convenient for customers. A quick fix, such as a fee review, may seem to make sense now, but in the long term will it be sustainable if you risk losing your clients’ loyalty? Instead, perhaps increasing the efficiency of online triaging and teleconsults – and charging properly for telemedicine work – would help maintain the right degree of revenue to stay buoyant. Whatever your approach, the emerging advice is that involving others in these decisions will bring the best results. Don't make assumptions about what your staff want, widen the discussion with the team, welcome ideas and bring staff along with you as changes take place. And, of course, it makes good business sense to ask your customers too, either directly in the consult room, on social media or through surveys. In her latest Covid-19 webinar, BVA president Daniella Dos Santos drove home these messages of inclusion but also stressed the importance of transparency. Being honest about the state of the business, the turnover and the ways of working will make the next year a lot more palatable and avoid any shocks. There may be tough times ahead, but with long-term solutions and some future-proofing planning now, we may reach the end of the tunnel that little bit sooner.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.213
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.004

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.115
GPT teacher head0.275
Teacher spread0.160 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2020
Admission routes1
Has abstractyes

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