Why deception with selective analysis of data and incomplete presentation of information continues to be the approach of choice: it has been proven to yield good short-term results.
MY foundation learning is in science. I always loved science subjects because I felt they gave me insights into how the world around me operated. I also appreciated the clear logic of science. You developed a theory, you devised experiments to test your theory, you collected and analyzed the data, and you came to a conclusion based on your analysis. Sometimes the results of the experiment proved and other times they disproved your theory.
I learned many things from my years spent in laboratories, experimental greenhouses and field stations. Among these, the following stand out. First of all, I learned that numbers do not lie; it is the people who report or interpret them who lie. Secondly, I learned that your analysis must be based on a large enough sample size for you to draw any conclusion with a reasonable degree of confidence. Thirdly, I learned that your experiments must be repeatable, and when they are repeated, under identical conditions, the results should not vary dramatically. If they do, the subject under investigation is too volatile for any firm conclusions to be drawn from just one or two experiments.
Where am I going to with this, you ask? Surely, I do not intend to give you a lecture on scientific experiments and data analysis on Facebook? Have no fear; the latter is definitely not my intention. Where I am leading you, however, is on a brief journey into the recent convenient use of statistics to arrive at a conclusion, in a manner that runs contrary to the three lessons I described above.
Less than one year ago, the Prime Minister of Saint Lucia announced with a high degree of glee and satisfaction that as a result of the policies that his government had implemented in the year since assuming office, unemployment levels had dropped from 21.4% (June 2016) to 16.8% by the end of the third quarter of 2017. The Prime Minister indicated that under his administration, in the short space of one year, he had been able to reduce unemployment by 25%. The math he used was (21.4-16.8)/21.4 = 21.5%; not quite 25% but close enough for the Prime Minister.
This claim by the Prime Minister provoked vigorous debate in many quarters. Those who support the Prime Minister and his administration praised the economic genius of the Prime Minister and his team and spoke glowingly of the confidence his administration had caused in Saint Lucia’s business community. Those who do not support the Prime Minister or his administration viewed the pronouncement with skepticism, bordering on incredulity. They could not reconcile the job creation numbers provided with the sectors or the communities in which they were said to have occurred. Many tried to identify the 5,000 new jobs that the Prime Minister indicated had been created in the third quarter of last year alone.
Responding to the sudden interest in maths and unemployment percentages and to questions about their validity, the Director of Statistics indicated that 6.7% of all the jobs created in the third quarter were “vulnerable jobs”. The Statistics Department went on to caution that ‘recovery in the job market needs to be confirmed by further quarterly declines in unemployment in the future’.
Since that pronouncement by the Prime Minister, not much more has been said by the government about the unemployment figures for our country. This made me curious. I thought that maybe the Prime Minister was waiting to make another big announcement later this year to provide further incontrovertible evidence of the efficacy of the policies and measures implemented by his government. Therefore, I did a little investigation of my own. After all, despite everything else that I have done since leaving university, I remain a scientist by nature — and what good is a scientist if he does not use his training? So, I put forward a theory, investigated, collected data, and set out to determine whether my theory was confirmed by the analysis.
What did my investigations reveal? Well, since that bold pronouncement by the Prime Minister that the 25% (sic) reduction in unemployment under his watch was a clear sign of progress, the unemployment levels have been: Oct-Dec 2017: 23.2%; Jan-Mar 2018: 21.8%; Apr-Jun 2018: 21.7%.
Now, if I were to apply the same logic to these figures as was applied by the Prime Minister last year, I would say that since his announcement, unemployment has increased by 29% [(21.7-16.8)/16.8]. I could also be forgiven for coming to the conclusion that under his watch, over the two years of his administration, unemployment has increased by 1.4% [(21.7-21.4)/21.4].
However, because I understand the importance of using statistics properly and more fundamentally, because I know that the unemployment problems plaguing our country, particularly among our youth, cannot be solved by piecemeal, incoherent policies and most certainly will not be resolved overnight, I will not succumb to the temptation to accuse the Prime Minister or his administration of worsening the unemployment situation since they assumed office.
There are two ways in which we can approach the governance of our country.
First, we can choose to educate and enlighten our citizens so that they are better informed, more employable (anywhere in the world), able to make better life choices and capable of making significant, meaningful contributions to the sustainable development of their communities and their country. This approach will help us solve our vexing, stubborn unemployment problem.
Alternatively, we can seek to deceive them with disjointed actions, poorly conceived ideas and unsustainable projects that look good in glossy print or in a PowerPoint presentation, provide great sound bites for television news, and offer fleeting ‘soulajman’.
The logical, science-based person in me knows and understands that the latter is a recipe for medium-term and long-term disaster of catastrophic proportions.
If the ‘sneaky politician’ in me was a dominant voice in my head, I guess I would understand why deception with selective analysis of data and incomplete presentation of information continues to be the approach of choice; it has been proven to yield good short-term results.
However, since I have been quoting proverbs the last few days, it is perhaps fitting that I should end with the caution of an old Danish Proverb: “After pleasant scratching comes unpleasant burning.”