We’ve just published a paper in PLOS ONE showing high infant mortality rates are contributing to an incessant rise of the global human population, which supports arguments for greater access to contraception and family planning in low- and middle-income nations.
In the first study of its kind, we provide a compelling argument that the United Nations’ Sustainable Development Goals for reducing infant mortality can be accelerated by increasing access to family planning.
Although it sounds counterintuitive, higher baby death rates are linked to higher population growth because the more babies a women loses, the more children she is likely to have. Family planning, including access to quality contraception, enables women to plan pregnancies better and therefore reduce infant mortality to curb the so-called ‘replacement’, or ‘insurance’ effect.
We evaluated six conditions thought to influence a woman’s fertility — availability of family planning, quality of family planning, education, religion, mortality, and socio-economic conditions, across 64 low- to middle-income countries.
My definition of a ‘lab’ is simply a group of people who do the science in question — and people are a varied bunch, indeed. But I wager that most scientists would not necessarily give much dedicated thought to the diversity of the people in their lab, and instead probably focus more on obtaining the most qualified and cleverest people for the jobs that need doing.
For example, I have yet to meet an overtly racist, sexist, or homophobic scientist involved actively in research today (although unfortunately, I am sure some do still exist), so I doubt that lab heads consciously avoid certain types of people when hiring or taking on new students as they once did. The problem here is not that scientists tend to exclude certain types of people deliberately based on negative stereotypes; rather, it concerns more the subconscious biases that might lurk within, and about which unfortunately most of us are blissfully unaware. But all scientists must be aware of, and seek to address, their hidden biases.
It is time to place my cards on the table: I am a middle-aged, Caucasian, male scientist who has lived in socially inclusive and economically fortunate countries his entire life. As such, I am the quintessential golden child of scientific opportunity, and I am therefore also one of the biggest impediments to human diversity in science. I am not able to change my status per se; however, I can change how I perceive, acknowledge, and act to address my biases.
The earlier scientists recognise these challenges in their career, the more effective they will be.
I acknowledge that as a man, I am already on thin ice discussing gender inequality in science today, for it is a massive topic that many, far more qualified people are tackling. But being of the male flavour means that I have to, like an alcoholic, admit that I have a problem, and then take steps to resolve that problem. After all, privilege is generally invisible to those who have it. If you are a male scientist reading this now, then my discussion is most pertinent to you. If you are female, then perhaps you can use some of these pointers to educate your male colleagues and students.
There is now ample evidence that science as a discipline is just as biased against women as most other sectors of professional employment, even though things have improved since the bad old days of scientific old-boys’ clubs. Journals tend to appoint more men than women on their editorial boards, and that editors display what is known as homophily when selecting reviewers for manuscripts: the tendency to select reviewers of the same gender as themselves.
Likewise, experimental evidence demonstrates that scientists in general rate male-authored science writing higher than female-authored works, and that academic scientists tend to favour male applicants over females for student positions. In the United Kingdom, as I suspect is more or less the case almost everywhere else, female academics in science, engineering, and mathematics also tend to have more administrative duties, and hence, less time to do research; they also have fewer opportunities for career development and training, as well as earning a lower salary, holding fewer senior roles, and being less likely to be granted permanent positions.
Back in April I blogged about an idea I had to provide a more discipline-, gender-, and career stage-balanced way of ranking researchers using citation data.
Most of you are of course aware of the ubiquitous h-index, and its experience-corrected variant, the m-quotient (h-index ÷ years publishing), but I expect that you haven’t heard of the battery of other citation-based indices on offer that attempt to correct various flaws in the h-index. While many of them are major improvements, almost no one uses them.
Why aren’t they used? Most likely because they aren’t easy to calculate, or require trawling through both open-access and/or subscription-based databases to get the information necessary to calculate them.
Hence, the h-index still rules, despite its many flaws, like under-emphasising a researcher’s entire body of work, gender biases, and weighting towards people who have been at it longer. The h-index is also provided free of charge by Google Scholar, so it’s the easiest metric to default to.
So, how does one correct for at least some of these biases while still being able to calculate an index quickly? I think we have the answer.
Since that blog post back in April, a team of seven scientists and I from eight different science disciplines (archaeology, chemistry, ecology, evolution & development, geology, microbiology, ophthalmology, and palaeontology) refined the technique I reported back then, and have submitted a paper describing how what we call the ‘ε-index’ (epsilon index) performs.
Happy Pride Month to the beautiful Queers of the scientific community, and beyond!
I decided to write this post to help non-queer scientists interact respectfully with their queer colleagues. When I was researching for this post, I noted very little in the way of written material on queer issues specific to the sciences, or indeed, many statistics. It’s for this reason I decided to provide you with this little primer.
Before we begin, I would like to clarify some language used below and in the queer community.
The letters: LGBTQIA+
You have probably seen varying combinations of the letters, the most common is LGBT, and the most modern and inclusive is LGBTQIA+. So, as someone who grew up watching Sesame Street, let us pay homage to my childhood.
L is for Lesbian
G is for Gay
B is for Bisexual
T is for Transgender
Q is for Queer
I is for Intersex
A is for Asexual
+ is for anyone in-between, a combination of some, variants of others, or still working it out
How I identify
I identify as a woman and my pronouns are, she/her/hers, and I am never offended by they/them/their pronouns. Read the rest of this entry »
I do a lot of grant assessments for various funding agencies, including two years on the Royal Society of New Zealand’s Marsden Fund Panel (Ecology, Evolution, and Behaviour), and currently as an Australian Research Council College Expert (not to mention assessing a heap of other grant applications).
Sometimes this means I have to read hundreds of proposals made up of even more researchers, all of whom I’m meant to assess for their scientific performance over a short period of time (sometimes only within a few weeks). It’s a hard job, and I doubt very much that there’s a completely fair way to rank a researcher’s ‘performance’ quickly and efficiently.
It’s for this reason that I’ve tried to find ways to rank people in the most objective way possible. This of course does not discount reading a person’s full CV and profile, and certainly taking into consideration career breaks, opportunities, and other extenuating circumstances. But I’ve tended to do a first pass based primarily on citation indices, and then adjust those according to the extenuating circumstances.
But the ‘first pass’ part of the equation has always bothered me. We know that different fields have different rates of citation accumulation, that citations accumulate with age (including the much heralded h-index), and that there are gender (and other) biases in citations that aren’t easily corrected.
I’ve generally relied on the ‘m-index’, which is simply one’s h-index divided by the number of years one has been publishing. While this acts as a sort of age correction, it’s still unsatisfactory, essentially because I’ve noticed that it tends to penalise early career researchers in particular. I’ve tried to account for this by comparing people roughly within the same phase of career, but it’s still a subjective exercise.
I’ve recently been playing with an alternative that I think might be a way forward. Bear with me here, for it takes a bit of explaining. Read the rest of this entry »
The last time I went surfing the waves were very slow and between sets I had a lot of time to contemplate life. This was when it occurred to me that the pursuit of a career in academic research was similar, in many ways, to trying to catch waves. Here are 11 surprising things surfing and academic research have in common:
1. It’s a constant struggle and a long, hard slog to get past the white water
Paddling out through the white water, having wave after wave come crushing down on you while trying to turtle-roll through the biggest ones, can be a real challenge. Likewise, in science it takes most people years of study, work (often unpaid), long hours in the lab, the field, and at the desk, to establish themselves and potentially secure employment for a period longer than a year or two. You find yourself working late finishing papers from research you did years ago (again, usually unpaid), or volunteering to get more hands-on experience because you know how important these things are. But you power on, always trusting that, just like paddling through the white water will help get you the stamina and shoulder muscles you need to catch waves, all this work will lay the foundation for your career and make you a better scientist.
2. Women are underrepresented and often treated badly (but it’s changing!)
Whether you look around you in the line-up at your surf spot or at a scientific conference, women are underrepresented. Many women I know have experienced discrimination related to their gender, as women are often not assessed based purely on their ability to shred or do high-quality research. Indeed, reviewers have an unconscious bias against women in science, and in surf competitions men get to compete when conditions are optimal whilst women are relegated to whatever is left. Nevertheless, slowly but surely, things are changing for women. It will still take many years to reach an equilibrium (if there is such a thing), but people are becoming more and more aware of the gap, and female researchers and surfers are pushing that glass ceiling.
3. Others always seem to be performing better than you
This is probably true for many areas in life! It always looks so much easier when others do it, and we tend to only see those who do better than us (also, imposter syndrome, anyone??). I guess it’s a lifelong task to learn not to compare yourself to others, to stay focused on your path and try to take inspiration from the achievements of others, rather than letting them demotivate you. Read the rest of this entry »
Female green turtles (Chelonia mydas) spawning (top) and diving (bottom) on Raine Island (Great Barrier Reef, Queensland, Australia) — photos courtesy of Ian Bell. This species is ‘Endangered’ globally since 1982, mainly from egg harvesting (poaching conflict in Mexico for olive ridleyLepidochelys olivacea featured by National Geographic’s video here), despite the success of conservation projects (39). Green turtles inhabit tropical and subtropical seas in all oceans. Adults can grow > 150 kg and live for up to ~ 75 years. Right after birth, juveniles venture into the open sea to recruit ultimately in coastal areas until sexual maturity. They then make their first reproductive migration, often over 1000s of km (see footage of a real dive of a camera-equipped green turtle), to reach their native sandy beaches where pregnant females will lay their eggs. Each female can deposit more than one hundred eggs in her nest, and in several clutches in the same season because they can store the sperm from multiple mating events.
When sex is determined by the thermal environment, males or females might predominate under sustained climatic conditions. A study about marine turtles from the Great Barrier Reef illustrates how feminisation of a population can be partitioned geographically when different reproductive colonies are exposed to contrasting temperatures.
Fortunately, most people in Western societies already perceive that we live in a complex blend of sexual identities, far beyond the kind of genitals we are born with. Those identities start to establish themselves in the embryo before the sixth week of pregnancy. In the commonest scenario, for a human foetusXY with one maternal chromosome (X) and one paternal (Y) chromosome, the activation of the Sry gen (unique to Y) will trigger the differentiation of testicles and, via hormonal pathways, the full set of male characteristics (1).
Absence of that gene in an XX embryo will normally lead to a woman. However, in just one of many exceptions to the rule, Sry-expression failure in XY individuals can result in sterile men or ambiguous genitals — along a full gradient of intermediate sexes and, potentially, gender identities. A 2015 Nature ‘News’ feature echoes two extraordinary cases: (i) a father of four children found to bear a womb during an hernia operation, and (ii) a pregnant mother found to host both XX and XY cells during a genetic test – with her clinical geneticist stating “… that’s the kind of science-fiction material for someone who just came in for an amniocentesis” (2). These real-life stories simply reflect that sex determination is a complex phenomenon.
The more I have tried to answer this question, the more it has eluded me. Before I even venture an attempt, it is necessary to distinguish the more esoteric term ‘effective’ from the more pedestrian term ‘success’. Even ‘success’ can be defined and quantified in many different ways. Is the most successful scientist the one who publishes the most papers, gains the most citations, earns the most grant money, gives the most keynote addresses, lectures the most undergraduate students, supervises the most PhD students, appears on the most television shows, or the one whose results improves the most lives? The unfortunate and wholly unsatisfying answer to each of those components is ‘yes’, but neither is the answer restricted to the superlative of any one of those. What I mean here is that you need to do reasonably well (i.e., relative to your peers, at any rate) in most of these things if you want to be considered ‘successful’. The relative contribution of your performance in these components will vary from person to person, and from discipline to discipline, but most undeniably ‘successful’ scientists do well in many or most of these areas.
That’s the opening paragraph for my new book that has finally been release for sale today in the United Kingdom and Europe (the Australasian release is scheduled for 7 April, and 30 April for North America). Published by Cambridge University Press, The Effective Scientist. A Handy Guide to a Successful Academic Careeris the culmination of many years of work on all the things an academic scientist today needs to know, but was never taught formally.
Several people have asked me why I decided to write this book, so a little history of its genesis is in order. I suppose my over-arching drive was to create something that I sincerely wish had existed when I was a young scientist just starting out on the academic career path. I was focussed on learning my science, and didn’t necessarily have any formal instruction in all the other varied duties I’d eventually be expected to do well, from how to write papers efficiently, to how to review properly, how to manage my grant money, how to organise and store my data, how to run a lab smoothly, how to get the most out of a conference, how to deal with the media, to how to engage in social media effectively (even though the latter didn’t really exist yet at the time) — all of these so-called ‘extra-curricular’ activities associated with an academic career were things I would eventually just have to learn as I went along. I’m sure you’ll agree, there has to be a better way than just muddling through one’s career picking up haphazard experience. Read the rest of this entry »
Another little expurgated teaser from my upcoming book with Cambridge University Press.
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My definition of a ‘lab’ is simply a group of people who do the science in question — and people are indeed a varied mob. I’d bet that most scientists do not necessarily give much thought to the diversity of the people in their lab, and instead probably focus more on obtaining the most qualified and cleverest people for the jobs that need doing. There are probably few of us who are overtly racist, sexist, or otherwise biased against or for certain types of people.
But the problem is not that scientists tend to exclude certain types of people deliberately based on negative stereotypes; rather, it concerns more the subconscious biases that might lurk within, and about which unfortunately most of us are blissfully unaware. But a scientist should be aware of, and seek to address, these hidden biases.
I acknowledge that as a man, I am stepping onto thin ice even to dare to discuss the thorny issue of gender inequality in science today, for it is a massive topic that many, far more qualified people are tackling. But being of the male flavour means that I have to, like an alcoholic, admit that I have a problem, and then take steps to resolve that problem.
Wildfires transform forests into mosaics of vegetation. What, where, and which plants thrive depends on when and how severely a fire affects different areas of a forest. Such heterogeneity in the landscape is essential for animal species that benefit from fire like woodpeckers. Anyone raised in rural areas will have vivid recollections of wildfires: the…
From time to time I turn my research hand to issues of invasive species control, for example, from manipulating pathogens to control rabbits, to island eradication of feral cats and pigs, to effective means to control feral deer. Not only do invasive species cost well over $1.7 trillion (yes, that’s trillion, with 12 zeros) each…
We’ve just published a paper in PLOS ONE showing high infant mortality rates are contributing to an incessant rise of the global human population, which supports arguments for greater access to contraception and family planning in low- and middle-income nations. In collaboration with Melinda Judge, Chitra Saraswati, Claire Perry, Jane Heyworth, and Peter Le Souëf…