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This type of environmental social information should be assimilated by the performer in order to become a task constraint [ 46 , 47 , 48 ]. In fact, this information cannot be defined without goal-directed organisms for which those rules and instructions are valid. It is important to note that instructions, themselves, are just third person e. This is one of the reasons why instructions do not have the same effects on all instructed performers. Tasks are understood here as a set of interacting task constraints.
As tasks and task constraints are distributed between the organism and the environment, they are necessarily emergent, either by design e.
Properties that exist only at systemic e. In other words, for a property to be emergent, the necessary and sufficient condition is not to be a property of the system components.
Note that this definition does not pose additional criteria to the system components properties and their interactions. Then, it is obviously incidental and not essential to the definition if the component interactions are designed, prescribed, or arise spontaneously, whether the system has central or distributed control or if the components have or do not a representation of the global system behavior.
The concept of emergent property has the same meaning for technical e. However, it is important to note that not all properties at systemic macro level are emergent. For example, the mass of a system is only an extensive property because its components have the property of mass themselves.
While in physical, chemical, and biological systems emergent properties arise dominantly through self-organization, in social systems, the interactions among components e.
On the other hand, e. This is because a large set of constraints and interactions between players change spontaneously, that is, they are not specifically designed or prescribed by the coach.
When these interactions change, the task changes as well. Thus, during matches, old task constraints decay and new task constraints arise. In this case, one can say that tasks self-design.
Task solutions, i. Additionally, actions emerge from the interaction between many other microscopic degrees of freedom acting at lower levels nervous system, muscles, tendons, bones, joints, etc. This means that while a change in a set of task constraints may have no visible effects, a further small change may produce a qualitative reorganization of the whole system [ 45 ].
For instance, while a substantial increase in the time on task may be adequately compensated through psychobiological synergies, an additional small increase in exercising time can suddenly produce task disengagement due to exhaustion [ 51 ], or a small deviation of the ball trajectory during a soccer match can lead to ball recovery and complete re-organization of both teams e.
Game dynamics, characterized by its transitions, changes in ball possession, space occupation, tactical patterns, play rhythm, etc. These sudden changes, products of the interactions between a set of task constraints, emerge as new tasks spontaneously via self-organization i.
Some constraints change slowly with respect to the macroscopic function they produce and thus have a long-lasting effect and may be experienced as constant [ 51 ].
Constraints that are slowly evolving with respect to some more rapidly evolving ones can be treated as fast with respect to some variable that evolves over a longer timescale. Organismic constraints evolve structurally and functionally through the interaction with environmental constraints and vice versa. Slow-changing environmental constraints shape slow-changing evolutionary organismic constraints or traits e.
In turn, relatively slow-changing organismic constraints, such as habits, affect slow-changing environmental constraints e. These are usually two-way interactions, which can be related indirectly e. Figure 3 shows some examples of organismic and environmental constraints with faster and slower rates of change. Classification of organismic and environmental constraints according its relatively faster or slower rate of change. Some examples are provided.
As the environmental information can either be actively perceived by the performer, e. For instance, perception of affordances may occur within fractions of a second, task goals within minutes, team strategies within hours, and competition rules within decades.
The rate of change of constraints is related to their timescale effects on behavioral variables. The faster a constraint changes, the shorter its effects on the behavioral variable, and vice versa.
The different timescales of evolution of organismic, environmental, and developmental ontogenetic and phylogenetic constraints were briefly acknowledged in previous research [ 5 , 34 ].
However, the nested organization of constraints in levels and timescales in human systems has only recently been discussed in the case of task constraints [ 37 ].
These authors showed that task constraints on motor behavior are distributed across many interacting time scales rather than being provided at a single common timescale. To date, most of the relevant research has been conducted on the problems of how a single or a couple of predominantly task constraints channelize certain behavior within a single time scale. Torrents et al. The exploratory capacity at the team level was significantly lower when professionals played in numerical superiority, and this was compensated by an increase in individual exploration and vice versa [ 52 ].
Due to the lack of research on the nested organization of constraints, more studies are needed to assess their multilevel effects on the behavioral dynamics at the level of players, dyads, and teams. At the player level, the teammate anthropometry has been shown to constrain the action of dribbling in 1-on-1 basketball sub-phases [ 53 ]. At the dyadic level, the distance to the nearest opponent constrains the pass options [ 54 ].
During a game, different solutions emerge from the influence of constraints interacting at different timescales, from short i. We were not able to find any previous studies discussing the nestedness of the whole set of constraints organismic, environmental, and task and their possible circular causality relation.
Our claim here is that in sports, all types of constraints, not only task constraints, possess this nested characteristic. Figure 4 shows an example of the multilevel nestedness and correlatedness of constraints. Values lasting decades constrain competition motivation which varies over a faster timescale e. Relative workloads are a nice example of action-scaled affordances that constrain the metabolic pathways.
Short-term goals constrain attention not only through top-down pre-planned strategies. Under a fast-changing constraints regime, as occurs during sporting competitions, goals e. Example of nested constraints operating at different timescales and correlated through circular causality.
The exact timescales given in the figure are only orientative e. The sequence of nested constraints represented in Fig. For instance, the goal of having a successful sport career lasts longer than the goal of winning a championship, winning a match, or winning ball possession during the match. We can refer to fatigue status as being acute days and recovering fast, or chronic months and recovering slowly, or define workloads in the short term session , mid-term microcycle , or long term season.
It is worth to point out here that one may find slow-changing constraints evolving over decades not only at social or personal level e. The manipulation of constraints has been widely applied in motor learning and sport training, and specifically in small-sided games [ 56 ].
However, due to the limited literature capturing the nested structure of game constraints [ 57 ] and the relation between such levels [ 58 ], the concept of nested organization of constraints is still under-researched. Constraints at upper levels slow-changing constraints subjugate those at lower levels faster changing constraints , which in turn form the constraints at the upper level circular causality.
As many of the levels are related through circular causality see Fig. On the other hand, fast-changing constraints such as affordances influence the performance level positively or negatively and consequently the goal motivation and values. Interventions at the slowly changing constraints level personal values, fears enable a supporting context for successful intervention at the rapidly changing constraints level goals, strategy, affordances which is a prerequisite for successful behavioral dynamics in sports practice.
In turn, a successful intervention at the level of fast-changing constraints affordances enhances slowly changing constraints motivation, goals, and values. The distributedness and emergence of task constraints, as well as the interdependence of constraints and their nested organization in levels and timescales, has some relevant theoretical and practical implications for planning interventions. Furthermore, the interdependence and nested organization of constraints offer some practical advantages.
An intervention in slow-changing constraints situated at upper levels e. Due to their long-term evolution, upper levels values, motivation, etc. If such long-term constraints [ 59 ] decay, the whole system of faster constraints decays, and vice versa, and if they enhance, the whole system of faster constraints is enhanced.
For instance, if a value such as active sports participation is high and stable, the motivation for practice increases, and thus, the context for manipulating workload properties volume, intensity, complexity and learning from affordances enhances as well.
Such increase in workloads and fast and accurate perception of affordances increase the likelihood of goal constraints achievement performance level and, due to the circular causality, back-propagates enhancing and stabilizing the motivation [ 60 ] and value given to sport practice. Through circular causality and back-propagation i. To prevent such drop-off and other nonlinear effects like sports injuries [ 21 ], the adequacy of task constraints i.
The nestedness of constraints can be found in other examples. A player constrained by the fair play value perceives different affordances than one who is not constrained by this fair play e. The fear of failure or fear of success [ 61 ], acting as slowly changing long-term constraints, affect competition goals and strategies, attention, perceived affordances, and eventually, performance.
Under this perspective, proposing, for instance, tasks detached from the game to activate specific metabolic pathways e. Coach instructions, as an environmental constraint, should be mainly addressed to processes developed over longer timescales, e.
Instructions imposing specific action solutions e. In turn, personal differences in cognitive abilities and motivational drivers can also produce changes in the effectiveness of instructions.
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