Bibliographic record
Abstract
The COVID-19 pandemic has taken a heavy toll on children, especially in terms of their mental health.1-3 For example, they are more likely to experience family violence,1 showing the known deleterious effect of stress on loving relationships. Parents and carers have been stressed by the pandemic, while also being responsible for the care, love and support of their children in a time of great uncertainty. Brisbane writer and journalist Trent Dalton, author of the compelling novel Boy Swallows Universe, sought to counter his own COVID-induced discombobulation by walking the streets of Brisbane for 2 months, asking passers-by to tell him their personal love stories. Then, for 2 weeks, he sat on a busy street corner in Central Brisbane at a collapsible table, with two second-hand chairs, a sign that read: ‘Sentimental writer collecting love stories. Do you have one to share?’, and typed up the stories on a blue Olivetti typewriter bequeathed to him by the son of a friend who had died recently. The result is his book Love Stories,4 a compelling collection of stories that vary from the mundane to the maudlin to the mesmerising, interspersed with Dalton's reflections on love and life. The first person he sent the book to, his wife Fiona Franzmann, commented: ‘Love is not for understanding’. Maybe not, but Dalton sheds some light on parental love, including the poignant aphorism, ‘I'll only ever be as happy as my unhappiest child’. The COVID-19 pandemic, with its emphasis on ‘social distancing’, has interfered with our normal relationships. We have been advised by public health experts not to hug each other. Even hugs with one's own children have suffered from concerns about transmitting the virus. Children have not been able to hug their school friends.1 Dalton discusses hugs, introducing us to the concept of the standard duration for a hug being 3 s.4 He bases this on research by Emre Nagy, a Scottish psychologist who analysed the duration of athletes' hugs at the 2008 Beijing Olympics (1.8 s between opponents, 3.8 with coaches, average 3.2 s). Until now, I had thought the 3-s rule referred to how long food could remain on the floor before being eaten, but Internet research tells me that it more usually refers to basketball (time allowed in the foul lane) or driving cars (safe time gap between cars). The research findings on athletes' hugs seem to lack relevance to normal human relationships. When John Bowlby developed his ‘attachment theory’, he suggested that children evolved to be born biologically pre-programmed to form attachments with others, helping them survive (Fig. 1).5 In support of attachment theory, we know that kangaroo care, whose main component is skin-to-skin contact between mother and infant, not only reduces hypothermia and sepsis in low-birthweight infants in resource-poor countries, but saves lives, reducing mortality by a third.6 We know that stressed adults are more susceptible to catching respiratory virus infections, work carried out at the Common Cold Unit in Salisbury, UK by virologist David Tyrrell, who in 1960 had been the first to describe coronaviruses.7 In adults, hugging reduces stress and protects against infection with respiratory viruses (influenza A and rhinoviruses).8 It is indeed ironic that we are not allowed to hug because of the risk of catching COVID-19, but hugging can protect us against respiratory virus infection. Of course, we must not forget the catastrophic world-wide economic secondary effects of COVID-19, leading to increased poverty, and hence poorer living conditions and starvation, especially in resource-poor countries, and affecting children most of all.1, 2 Opportunities for showing love will inevitably be displaced by desperation in seeking food and shelter. We all have some healing to do, even while the pandemic continues to evolve, children perhaps most of all. Many parents continue to express great concern that they have been unable to prevent the adverse effects of the pandemic on their children.1 Let us hope that Canadian-based philosopher Matshona Dhliwayo is correct when he writes: ‘Time heals some wounds, but love heals them all’. The risk of catching COVID-19 from a hug is greatly reduced by COVID vaccination.1 Hugging our children and our friends again is one way of showing them how much we love them in the time of COVID. The author thanks Ken Nunn for inspiration on the topic of hugging, and Cathrine Congdon, Emily Isaacs, Stephen Isaacs, Henry Kilham and Ken Nunn for hugely constructive comments on earlier drafts of this editorial.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.009 | 0.010 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.015 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".