Many have argued that anti-doping requires increased funding to improve its impact. This argument, although tempting, may not present value for money, even if it is valid. Although recent empirical studies suggest that the prevalence of doping in sport far exceeds current detection-levels (see e.g., Striegel, Ulrich and Simon, 2010), and an increase in the funding for (and frequency of) testing might increase the hit-rate, I have yet to see a business case to demonstrate the cost of raising the hit-rate to an acceptable level, or even a clear statement on what such a rate might be.

WADA and the NADOs have other tools at their disposal, such as reliance on law-enforcement approaches (which they do not directly fund), and athlete education, but the majority of anti-doping effort (and expenditure) still goes on analytical approaches and creating the legal and scientific basis for a testing and punishment regime. Take for example, as an example of a NADO which has been applauded for its educational programme, UKAD: the budget from 2011-2015 was set at £29m: out of this only around 2m was assigned to educational activity, as opposed to 7m on athlete testing and a further 7m on results management. Similarly poorly off is the scientific activity supported by UKAD, set at 1m; even intelligence efforts are pegged at only 2m. Just under 50% of the UKAD budget (14m) goes on testing and results management (although the latter would also include management of non-analytical positives).

In order to better understand what an increased spend on anti-doping might look like, and why things are not that simple, imagine that all athletes covered by WADA are tested for blood and urine across a range of banned substances every time they compete, and at some agreed level of random out of competition testing. In addition all other efforts ramp up proportionally. Now imagine this has a much lower level of false negatives (i.e. approaching 8x as effective in detecting doping). Leaving aside the enormous cost and practical issues this might bring it is certain that this would not eliminate doping, merely reduce it, and would bring with it an increase in false positives. Would this be an end worth aiming for?

Of course, testing and punishment are not designed to catch everyone, they are intended to be sufficiently sensitive and draconian to offset the potential gains of doping. Anti-doping is intended to scare cheats into compliance, or at least to reduce incidence to such low levels as to be acceptable. I would speculate that current levels of sensitivity are insufficient to achieve this, but it is not clear that greater sensitivity would ever eradicate doping, even with the penalties currently imposed.

It is instructive to turn to another area of applied ethics to better understand these issues. In some universities it is expected that every piece of assessed work by every student be checked for plagiarism, both using automated and human techniques. Estimates of the incidence of plagiarism vary wildly, but Park (2003) argues that around half of a given student population might be expected to cheat in some way during their studies, and plagiarism is the most common form of cheating. There is a large investment in software to help detect plagiarism, and additional and substantial investment in ensuring that plagiarism is not a result of any misunderstanding of good academic practice. Penalties for plagiarism vary between institutions and are often nuanced to reflect the perceived seriousness of an offense: a first offense might receive a warning, but a second offense or aggravated example might to lead immediate expulsion. These measures demonstrably reduce the incidence of plagiarism.

Despite all this, students still plagiarise, sometimes with full conscious awareness of what they are doing and the probable consequences if caught, sometimes out of ignorance. This is probably because whereas for most students the decision to either intentionally cheat or fail to attend to instruction is driven by a fairly rational cost-benefit analysis, there is a minority that can both be identified as fitting a particular type of personality and will probably persist in repeating similar offences even if caught and given a minor penalty, additional academic support and education about the consequence of re-offending (Caruna, Ramaseshan & Ewing, 2000; also see Park, 2003 for a broader consideration of personality considerations). If this is true, then the most intent on cheating simply need to be identified and removed from a social context to which they are unsuited. This does not mean that the efforts to identify the remaining ‘strategic’ cheats are best replaced simply by better pro-active education. The fear of being caught and punished is for this group a significant motivation to comply as long as the detection rate is sufficiently high. Moreover, such detection techniques can themselves be used to educate students about good academic practice.

Even with all this effort, the detection rate does not nearly approach a zero rate of false negatives. This is why many institutions have actually chosen to downplay efforts to directly combat plagiarism and instead work towards education about ethical practices, embedding this within all educational activities. Students sign up to agreements which positively identify work as their own, and more general agreements on good conduct (honour codes, student contracts, partnership agreements). Such approaches seem to be effective in reducing the incidence of academic misconduct of all kinds (Park, 2003) especially where such efforts are the result of a partnership between students and faculty, but there is an implicit assumption that there are two types of offender – one that will respond to pro-active or reactive influences, incentives or penalties; and one that will wilfully continue to offend.

I am becoming persuaded that although detection and deterrence are important, and can play a role alongside education, pro-active positive identification and reinforcement of ethical behaviour is more fundamental. It is for this reason that we teach students about good practices in attribution before we teach them about malpractice, and I hope that this is why I see few cases in the work I assess. Of course, as with doping, it is near impossible to judge how good our efforts are without accurately judging the incidence of academic misconduct, and this is as yet unclear, partly because the incidence of plagiarism is related to an institution’s efforts to combat it.

How does this help us with competitive cycling: I wonder whether personality-screening should play a bigger role in anti-doping. There are ethical issues to overcome, but a voluntary approach such as that proposed by the Clean Protocol might go some way towards thinking outside what seems to be an unwinnable war of post-hoc detection and punishment. Alongside education about ethical values there is an opportunity here to work with the psychological aspects of cheating long before someone first dopes or tests positive.