Introduction

Ever think about thinking? It’s a lot to think about.

I’ve been working on the epistemology of training post(s), and boy, it’s a big topic. I knew that going in, but I keep finding myself wanting to do more research before committing anything to the page. I think that’s the right call in this case, but I also want to keep some momentum going with the blog, so I decided to put together a shorter post on a related concept, which I will term epistemological ease. By use of the word “epistemological”, I mean to imply that the concept will be centered around knowledge and belief in training, and by use of the word “ease”, I mean to imply that the concept aims to help us write and implement programs which maximize our ability to collect, analyze and utilize the information gleaned from the execution of the program.

Epistemological Ease and Justified True Belief

In the pursuit of epistemological ease in training, we strive to structure, implement, and interact with programs in ways which give us the greatest access to truth and the most justification in believing something to be true.

In thinking about the epistemology of training, I am using the justified true belief model of knowledge. The understanding of knowledge as justified true belief is by no means settled, and there are numerous problems with the idea – some which may even be relevant to knowledge in training. For the purposes of discussing and implementing epistemological ease, however, the JTB model is sufficient.

The Stanford Encyclopedia of Philosophy illustrates the justified true belief model as follows (1):

S knows that p if
(i) p is true;
(ii) S believes that p;
(iii) S is justified in believing that p.

The implications of this model are that S cannot know that p if (i) p is not true, (ii) S does not believe that p, or (3) S is not justified in believing that p. In english: you can’t know something that is false, you can’t know something you don’t believe, and you can’t know something that you don’t actually have rational justification for believing. Below, I will present concepts and strategies for maximizing our access to truth in the sphere of training.

III. Program Design and Implementation

The first step in creating conditions of epistemological ease is to structure programs in such a way that you can utilize the information derived from their implementation as easily and readily as possible. The most effective way I have found to ensure this is to write self-contained programming.

Programming is self-contained insofar as the decision-making process between exposures to a given stressor is informed by data gleaned from within the cycle itself, as opposed to drawing on information external to the particular training cycle. Contrast the two following squat progressions:

Note: 5 @ 8 = a set of 5 with two reps left in the tank, 5 @ 9 = a set of 5 with one rep left in the tank. This is a rate of perceived exertion (RPE) method derived from Mike Tuchscherer and Reactive Training Systems.

The self-contained program is only dependent on the athlete's state on the day of training, rather than measuring against some previous metric which will have necessarily limited applicability at any given time. This offers at least two advantages over the externally contained program. First, it allows the athlete to work to the best of their ability on the day, rather than holding them to an external standard. This is best not only for the athlete's safety and longevity (by allowing them the flexibility to push for a harder stress when they are able to or to back off to a lower stress when necessary), it is also better for the athlete's mental state – they are invested in the process rather than an arbitrary goal. If the task is to squat a set of 5 @ 9, they can complete that task regardless of what the weight is. If the task is to squat sets of 5 with 82.5% of 1RM and that proves to be too much for the athlete on the day, they may leave the gym feeling that they have failed to complete the day's training.

Second, the information gleaned from the athlete's day-to-day and week-to-week results on the self-contained program is more relevant and applicable than the information gleaned from the externally contained program. This is because what an athlete did on any given day is of limited relevance to what they did or will do on any other day, and the further in time those days are removed from each other, the less relevant to each other they become. If a athlete set a 1RM back squat 12 weeks prior to today's workout, there are 12 weeks of variables between the two, each of which may impact the athlete in such a way as to reduce the relevance of the established 1RM. By implementing a self-contained program, the athlete is able to perform the workout based on the most currently relevant information. Even if the program is stretched in order to base workouts on the previous week, that is still far more relevant than basing workouts on metrics established multiple weeks or even months ago.

Ultimately, all of this is the case because of a rarely discussed or understood aspect of programming: the training program is a proxy for a training effect. The program has no ontology of it's own. When we write a program, what we are actually doing is presenting the athlete with a stressor or series of stressors which will elicit a specific adaptation. The program is the codification of our understanding of the response between certain stressors and certain adaptations in a format which is easy to communicate and for the athlete to follow. The first workout in both the self-contained progression and the externally contained progression could be expressed as follows:

Perform a movement focused on hip and knee flexion followed by hip and knee extension, while isometrically stabilizing the trunk. Use a rep range and load selected for submaximal but relatively high force production, relatively low velocity, and moderate hypertrophy adaptations. Keep all sets submaximal, and perform a total volume of twenty working reps.

But this is not only a tremendously inefficient use of language, it is also likely to be very confusing to the athlete – even if she is reasonably well educated with regard to effective training practices and the reasons behind them, there are myriad ways which this statement could be taken, as indeed there are myriad ways to accomplish the intended effect.

Nonetheless, the prescription "Back Squat 5 @ 9, plus three down sets (load drop -10%)" is precisely a more efficient way of expressing the description above. The purpose of the workout is not to complete the workout, but to elicit the adaptations referred to therein. Further, those adaptations will be more or less the same whether the athlete performs the work sets with 290 pounds, 300 pounds, or 310 pounds. The difference in load is marginal with regard to stress imparted to the athlete – so why do we bother tracking it at all?

We track it because it is informative. It gives us a glimpse into how the athlete is responding to their training, and with enough glimpses, we can make more effective decisions about how to manipulate the program for better results. It follows that if these quantifiable metrics are important primarily for their informative value, the athlete is best served by a program which allows the information to be as relevant to their current status as possible.

Once the program is written in a self-contained manner, it must be implemented in such a way as to further the goal of maximizing epistemological ease. To this end, the athlete or coach must have an established protocol of bottom-up management.

Bottom-up management just means that the program is modified based on the athletes day-to-day and week-to-week results. Obviously, this goes hand-in-hand with self-contained program design. The self-contained program ensures that the information at hand is maximally relevant, and bottom-up management enables us to leverage that information quickly and effectively, since it is based entirely on the athlete's actual results, rather than on general principles of training.

This is not to suggest that general principles of training should not be applied – only that they are applied responsively. In other words, bottoms-up management means that we take the athlete's results, use our understanding of training principles to determine how to modify the (self-contained) program, and then implement those modifications. Rinse, repeat.

As the language suggests, the opposite of bottom-up management is top-down management. In a program which is managed from the top down, general principles of training are applied to the athlete before the athlete actually implements the program. If the program is self-contained, this is less of a problem, but it still prevents challenges which can be mitigated or eradicated with bottom-up management. First, general principles of training describe the general relationship between a given stressor and a general adaptation, but they definitionally cannot describe the precise relationship between that given stressor and a particular athlete's particular response. This means that we can design a program with those principles in mind, but unless we manage it from the bottom-up, the athlete will always be beholden to general principles absent the reality of individual variation.

This may seem obvious in theory. But what many coaches and athletes lack is an established protocol for bottom-up management. In other words, while they may make modifications to the program based on the athlete's day-to-day or week-to-week results, they lack an established protocol for doing so. This makes it much harder to determine what changes are most effective for any individual athlete, and further makes it harder to amalgamate data in such a way as to refine our understanding and application of general principles.

Good athletes and coaches already, often intuitively, utilize principles such as self-contained programming and bottom-up management in order to establish conditions of greater epistemological ease (even if they are unaware that they are doing so.) By becoming conscious of these tacit tendencies, organizing them, and applying them with intent, the collection, analysis, and implementation of athlete results becomes a more efficient and effective process.

Bibliography

(1) Ichikawa, Jonathan Jenkins and Steup, Matthias, "The Analysis of Knowledge", The Stanford Encyclopedia of Philosophy (Fall 2017 Edition), Edward N. Zalta (ed.), URL = <https://plato.stanford.edu/archives/fall2017/entries/knowledge-analysis/>.