Before we move on to the chapter where we'll examine a more complex risk equation than the classical one, and analyze the role our experience plays in it, let's first clarify the concepts of risk addition and subtraction.
Risk addition poses a specific problem that warrants separate consideration.
We have inherent risks and generated risks. They can lead to events. From the chapter on risks, we've learned the following:
A) Events are inevitable
B) Risks always add up
The fewer the sum of risks, the lower the impact of the event on us. However, the force of the event may initially exceed our capabilities.
Let's start with an example: we're crossing a pass, and a rock falls on our head.
It's known that many tourists have crossed passes without ever being hit by a falling rock. Nevertheless, empirical experience shows that if a tourist hikes passes of category 1B...2A and above every year for 15 years in different regions, it's almost certain that they'll be hit by something falling from above at least once. Maybe a carabiner, ice axe, or a partner's boot. Or even crampons. Very rarely - intentionally )) If someone claims it hasn't happened to them, it means they just don't remember the last time it did. For an experienced tourist, selective memory loss is normal.
The same empirical experience of hiking in the same region over many years shows that there are years when everything is falling apart, even things that previously seemed reliable and stable.
The conclusion is: in the mountains, things are always falling. They just don't always fall on us. However, if we hike long enough, sooner or later something will fall on us. If there's a possibility of something falling from a pass, and we hike passes, then eventually something will fall on us.
Even if the object is small, but its falling height (and thus speed) is high, we can be killed if we're not wearing a helmet. Low-impact events occur much more frequently than high-impact ones - smaller rocks fall more often than suitcases and travel farther than the main line of fall that we try to avoid. Add to this our possibility of simply slipping and sliding down a steep scree slope, and being stopped by a larger rock. Sometimes, in such cases, the rock becomes a tombstone with a plaque attached.
As a result, if we don't wear a helmet 100% of the time when necessary, and continue to hike "normal" passes, we'll eventually die or get injured with a probability close to 100%.
If we wear a helmet in 50% of necessary cases, we're playing roulette. As practice has shown, a rock can fall from a leader on a seemingly safe slope. Once, I dislodged a rock on my partner on a grassy slope, and he somehow managed to hit it with his head. He finished the route with a head wound. The rock didn't survive the impact - it shattered. That was a rare case where someone's head was stronger, but I've never seen another head that strong.
Nevertheless, as the mass of the rock increases, the protection offered by a helmet weakens. The force of the event can exceed the strength of our helmet and neck. Still, since high-impact events occur less frequently than low-impact ones, wearing a helmet significantly reduces the overall risk.
One of the corollaries of the chapter on risks states: in the addition of inherent and generated risks, generated risks play a decisive role in the vast majority of cases.
danger = risks + concern
danger = (inherent risks + generated risks) + concern
danger = (IR1 + IR2 + ... + IRn + GR1 + GR2 + ... + GRn) + concern
What's not considered in the chapter on risks in this equation?
That equipment, training, and preparation quality can work not only to: a) reduce risks (lowering the numerical value of some risks), b) increase risks (increasing the numerical value of some risks); but also to: c) subtract risks (one of the risks is completely eliminated or changes its quality), d) add risks (a new risk is introduced or an existing one changes its quality).
For example, a helmet taken on a route with falling rocks serves to subtract risks. If we take an ultra-light Chinese tent for overnight stays on a winter mountain plateau, we're more likely adding risks, regardless of our experience with it.
Similarly, with actions on the route: building a snow wall to protect our tent (even if it's an extreme one) subtracts risks. If we don't build it, we're adding risks.
The boundary between increasing (reducing) and adding (subtracting) is often thin and individual.
A non-obvious and individual example: if our ski bindings and skis allow for better control during descent, it doesn't mean we're guaranteed to be safer. In some cases, we might generate more risks by descending too quickly, increasing the likelihood of injury after a potential fall. Again, this doesn't mean good bindings have no place in ski hiking; it means we need to match our equipment to our experience and skills, and work with our concern. A higher level of concern, with proper experience, leads to caution and reduces risk.
A good analogy is a sports car: the faster we need to drive, the more prepared and racing-ready it should be. But the more prepared and racing-ready it is, the higher the likelihood of an average driver hitting a nearby pole. Twenty years of experience driving a regular car won't help. They need a different kind of experience.
The same piece of equipment, as well as a higher level of skill and physical fitness, can work in either direction in the risk equation. Moreover, advanced equipment and top-notch physical fitness significantly affect our level of concern, and at some point, this concern drops so low that caution disappears, and risks increase sharply.
(Hence, concern in the equation is more like a correlation coefficient)
The main problem is that adding and/or increasing generated risks often happens unconsciously, and we can't always control them. This is one reason why high-tech and reliable equipment for complex and extreme hikes always requires more experience. It has hidden drawbacks for inexperienced athletes, but deceives with its reliability, which requires that very experience to be realized. Realizing reliability means subtracting and reducing risks.
A consequence of this problem: participants can hike for a long time with the wrong tactics, strategy, and inadequate equipment. In other words - with the wrong approach. As we know from the chapter on risks, not all risks lead to events. They only provoke them, and risk is always an uncertain condition.
Let's consider three common examples:
- Most ski tourists and ski mountaineers who buy ski touring harnesses, ropes, and hardware don't know how to tie into a rope and don't know that they need to tie a knot at the ends of a rappel rope. They take the equipment on the route "just in case."
(They subtract a certain risk, but the generation of risk as circumstances and weather worsen in a potential event can be comparable to the risk they subtracted)
- Most buyers of avalanche beacons can't actually search for (or search quickly enough) a victim because they ski or hike with a guide or an experienced leader. They buy a beacon so that others can find them. If they undergo mandatory training (for release on the route), it's often not retained in their memory due to a psychological barrier.
(In general, the situation with avalanche beacons is a checkmate - each buyer hopes that others will be better at searching)
- Most ski tourist groups in the mountains don't use avalanche beacons at all. And indeed, why do they need them? Our grandparents hiked without them, our parents hiked without them, and we've been hiking without them for 20 years.
(Here, the situation is indicative: not having an avalanche beacon means that in the event of an avalanche, we will almost certainly die. That is, having or not having a beacon [as a generated risk] in the risk equation has such a high value that it immediately and unconditionally comes down to life and death, without any alternatives - and examples of those who died specifically because their group lacked beacons are truly endless)
Due to the uncertainty of conditions, we can lose (enter a critical event) due to our approach at any moment - it can happen on the first hike, or on the tenth.
At the same time, we're dealing with the dynamics of the system: if a group doesn't lose on the first or second route, by the tenth, they may have changed part of their conditionally incorrect approach to a conditionally correct one. But the opposite is also true: by the tenth route, it's possible to change part of the correct approach to an incorrect one. This answers the question of why accidents related to generated risks happen, including to very experienced athletes.
(Therefore, the best experience is one based on small and medium-sized mistakes. Experience based solely on luck can be incorrect and dangerous)
The uncertainty of conditions leads to the following:
-
The more routes we hike, and the more complex they are, the higher the likelihood of an accident happening to us. The complexity has less significance (but still has some). Analysis of accidents shows that experienced athletes die, including in very simple hikes. That is, the sum of risks on a particular simple hike can be even higher because it's "simple." After all, we ourselves build the danger equation, not just the terrain and weather.
-
Statements based on "I've been hiking like this for 10 years" are not always objective or true. They can be taken into account, sometimes even should be, but we need to think for ourselves.
The equation
danger = (IR1 + IR2 + ... + IRn + GR1 + GR2 + ... + GRn) + concern
always forms the individuality of each group at a given point in time.
And yet, there are important nuances.
An accident or incident on a hike is one of the events on the route, either standalone or following a previous event. An event, in turn, is often a process.
A process can proceed with average risk values, or it can contain extreme risk values.
How do they differ?
With average values, the probability of death (an accident doesn't always lead to death) of a participant or participants is low, and the accident occurs due to a combination of values. That is, we can add up many small risks, both inherent and generated, and get a critical event. A critical event leads to a subsequent chain of events, and death, if it occurs, is due to the overall sum.
Extreme risk values form a "life-or-death" variation in a single event. That is, if the event occurs, someone dies. Rarely - it's limited to severe injuries.
In the presence of extreme risk values in the danger equation, other terms have little significance. We can be a very "experienced" team, but if an avalanche hits us and we don't have avalanche beacons, the probability of survival for the victims is more a matter of chance. Someone's death is a predictable outcome.
Imagine a certain ice route. A novice with limited experience climbs it with bottom rope and falls. Their death or injury depends on the sum of risks: how well the anchor and intermediate points are set, how correctly they tied in, at what point relative to the first points they fell, and so on. They can be as inexperienced as they like, but the probability of their death is not entirely clear-cut, and they and their partner need to make many mistakes for the sum of risks at that moment to lead to death. Injury is more likely, but not in all cases will it be severe.
Now, let's look at an experienced climber who climbs the same ice solo without a rope. If they fall, their death is guaranteed. Other risks in the equation play a role in the causes of the event - they may fall due to premature fatigue caused by previous days. But they're still in an equation with an extreme risk value. Yes, the event may not occur, but if it does, the outcome is certain. They have no rope or protection, and they'll fall all the way to the bottom.
In the case of avalanche danger, as a solo climber, I always introduce an extreme risk value into the equation. If an avalanche occurs, I die. That is, my mistake in assessing the avalanche risk of the slope leads to a single outcome. But a group that doesn't use avalanche beacons on an avalanche-prone route also introduces an extreme risk value into the equation. We become equally vulnerable, and our ability to predict avalanches will now be decided by the terrain alone.
This is an interesting point: in a group, by making a small improvement in tactics and using one piece of equipment, we can eliminate the extreme value from the risk equation. At the same time, if we don't know how to use a beacon when searching or ignore studying slopes for avalanche risk (a beacon, strangely enough, doesn't hold snow on the slope by itself), we can die due to the sum of risks with average values.
When preparing for a route and during its passage, it's desirable to identify extreme risk values and eliminate them if possible, and then reduce the remaining average values so that their sum is smaller. This is understandable from a mathematical point of view, but it's not always clear how to do it in practice.
As we noted above: adding and/or increasing generated risks often happens unconsciously, and we can't always control them. In other words: directly on the route, we're often limited. It follows that preliminary preparation for the hike becomes crucial: it instills templates, instructions, and algorithms in us. Sometimes this preparation is simple, sometimes complex - it all depends on the specific route. The quality of preparation for the route is directly linked to the sum of risks on the route. The quality of preparation doesn't directly depend on the time spent on it - time alone doesn't guarantee quality.
It should be understood that inherent risks can also have extreme values. If a random, untriggered suitcase falls on us from a cliff, the outcome is obvious. The suitcase doesn't care who it falls on, a novice or an experienced climber. The presence or absence of a helmet becomes irrelevant, as do the state of the rope and other protection - for the person it falls on, other factors cease to matter.
On complex peaks in mountaineering, like Pobeda, the number of extreme inherent risk values is extremely high, making it impossible to eliminate them. That is, some routes offer the possibility of dying at any point, regardless of experience and preparation. Another issue is that generating risk on such routes is also close to extreme values.
In turn, if high risk generation is inevitable, and extreme inherent risk values can't be eliminated, we're forced to consciously generate additional risks to reduce the likelihood of being affected by extreme inherent risks. A classic example is increasing the speed of route completion. Speed = safety. In particular, if a falling object is inevitable, the less time we spend on its probable flight path, the safer we are overall. Speed, as one example of combating extreme values, always affects risk generation and is therefore a separate tool that needs to be mastered - to generate risks of lower values.
Comments
Sign in to leave a comment