Doug Campbell (RiP) Did the PFD GMHS Know or Ignore his Tried-and-True Campbell Prediction System? 3
This preferred Title replaces the Wix website size constraints version - "Doug Campbell (RiP) Did the Prescott FD Granite Mountain Hot Shots (GMHS) Even Know, Train In, or Ignore his Tried-and-True Campbell Prediction System leading up to and including their detriment on June 30, 2013? Part 3 of 4"
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Abbreviations used below: Wildland Firefighters (WFs) - Firefighters (FFs).
The author took the liberty of correcting some of the minor spelling, punctuation, and grammar errors in the sources provided; and also provided select links and/or hyperlinks as well throughout this post to the best of the author's abilities. They will show up in an underlined, somewhat faded appearance. Clicking on the link twice will reveal a blue link which will take you to the source after clicking on it again.
Carried over from Part One and Part Two - Doug Campbell passed away in Ojai, CA on July 13, 2021. This is a tribute to our self-avowed Politically Incorrect Hot Shot Friend and Brother, Mentor, Leader, Visionary, and Creator of the Campbell Prediction System (CPS). Doug Campbell (RiP) was truly a remarkable man with a wide range of wildland fire interests in fire behavior, leadership, and human factors; enhanced by always being grounded by family, friends, loved ones, and colleagues. Whatever he did, he did it with eagerness, enthusiasm, and enjoyment. He was always respectful and always logical. He was at ease "speaking truth to power" for the benefit of all WFs and FFs.
He taught us to think of the predicted fire behavior intuitively, in terms of logic. Doug was truly blessed with an incredibly brilliant mind, equipped to reach the highest intellect, and yet still able to identify with and relate the simple aspects of reading a wildfire's signature to discern what it was telling us. He died, much too soon. However, many of us were blessed to have attended his lectures and read and researched, and then applied his works. And this is what was to eventually become the Campbell Prediction System (CPS). We promise to pass this "Old School" work on to others. Thank you. We will miss you.
No king is saved by the multitude of an army;
A mighty man is not delivered by great strength.
A horse is a vain hope for safety;
Neither shall it deliver any by its great strength. Psalm 33: 16-17 (NKJV)
"Ninety percent of success can be boiled down to consistently doing the obvious thing for an uncommonly long period of time without convincing yourself that you're smarter than you are." Farnam Street Blog (8/8/21) "Learn faster, think better, and make smart decisions - Wisdom You Can Use"
Figure 1. Doug Campbell and CPS images. Source: Wildfire Management Tool WWEC website
Carried over from CPS post Part Two within the CPS documents - USFS Project Leader Dr. Ted Putnam's Findings From the Wildland Firefighters Human Factors Workshop - Improving Wildland Firefighter Performance Under Stressful, Risky Conditions: Toward Better Decisions on the Fireline and More Resilient Organizations (Table of Contents)
Consider now the works of several recognized "experts" in human factors. Appendix D. - Keynote Presentations. (1) Dr. Curt C. Braun Department of Psychology, University of Idaho addressing the Behavioral Bases of Accidents and Incidents: Identifying the Common Elements in Accidents and Incidents. (2) And Dr. Klein from MacroCognition LLC addressing Recognition Primed Decision Strategies. (3) And David O. Hart, TID, Inc. addressing the Cultural Attitudes and Change in High-Stress, High-Speed Teams. (4) And Dr. Karl Weick University of Michigan addressing South Canyon Revisited: Lessons from High Reliability Organizations.
First off, posted elsewhere on the YHFR website, Dr. Braun was our Human Factors expert on the "Hochderferrer Fire Shelter Deployment Investigation" on the Coconino NF in 1996. Spelled incorrectly on the Wildland Fire LLC web search result (HOCHDERFTER FIRE SHELTER DEPLOYMENT), the report, and associated documents of the fire, are included as a link in the fire name above. This link with further information is from USFS Fire Analyst Rick Stratton's Wildland Fire Library website describing it as an "event."
Note the letter content and the handwritten comment on the cover page about "the releasable portion/part of the report."
This author was the Operations Specialist. And Dr. Braun's comment was part of our initial human factors briefing. "The first thing we're going to do is establish a conclusion, then find the facts to support it." This author questioned that statement and stated that the facts should come first as they were supposed to lead us to a conclusion. Braun insisted that the conclusion would come first. "Then we can write anything we want" was this author's response. The statements in Dr. Braun's presentation belie his conclusion's first principle.
Notwithstanding the above comments, and his 2001 research with others of a similar ilk, where they basically undermine the collective intelligence of FFs and FFs seeking an alternative to the Fire Orders ( Creating and Evaluating Alternatives to the 10 Standard Fire Orders and 18 Watch-Out Situations, International Journal of Cognitive Ergonomics - 2001). And this is supposedly because there are what? Simply far too many items to remember? Dr. Braun has contributed some valid points in his presentation here below. So then, this question needs to be broached: How did all of you make it through high school and college without memorizing 43 key principles that will save your lives? Or how about all of you sports aficionados that can memorize hundreds of sports players and teams statistics?
(Heading and section emphasis are original. All other emphasis is added below. The word decision-making is unhyphenated in the original and now hyphenated throughout this YHFR post, to avoid the annoying spellcheck reminders to hyphenate the word)
Behavioral Bases of Accidents and Incidents: Identifying the Common Elements in Accidents and Incidents
Dr. Curt Braun - "Virtually every college student has faced the philosophical question, "If a tree falls in the woods and no one is there to hear it, does it make a sound?" The answer of course is no; the falling tree does not make a sound. While many people struggle with this answer, it is important to remember that the answer relies, not on the physics associated with a falling tree, but rather on the definition of sound. Sound is a subjective sensation created when the ear is stimulated by changes in the surrounding air pressure. Given this definition, a tree falling in the woods makes no sound when an ear is not present. A comparable safety question might be, "If there is a snag in the woods and there is no one there, does it pose a risk?" Again, the answer would be no. As with the sound example, the answer centers not on the physics of a falling tree, but rather on the definition of risk, a chance of loss or injury to a human. In the absence of a human, a falling snag creates no threat of injury or loss. Although this relationship appears obvious, it is important to realize that there are two components to this question: the snag, and the presence or absence of the human. Both play a role in creating a risky situation.
Here are a few sources countering the "if a tree fell in the forest" question for your consideration and perusal if you're interested in this ongoing philosophical, scientific, hypothetical argument - for hundreds of years.
February 28, 2018. Written by: Michael Bahtiarian. If a Tree Falls in a Forest: A Yes and No Answer? Acentech
K. Cornille. Apr 1, 2018, (link in author's name and date) If a Tree Falls in the Woods. It’s okay to not know what happens. Medium.com
Jim Baggott February 14, 2011, Quantum Theory: If a tree falls in the forest… Oxford Unified Press
Numerous commenters. ETHICAL CONUNDRUMS. The Guardian UK: If a tree falls in the forest and no one is there, does it still make a sound?
If an individual is injured by a falling snag, clearly both had to be present. This situation can easily be represented by the following model:
Environmental Hazard (Snag) + Human = Accident
The role of the snag and the individual in this situation are (sic) significantly different. The fact that the snag will eventually fall is well known and in contrast to the actions of the human, represents a relative constant. We know that the snag will eventually fall, but not when. If the environmental hazard remains essentially constant, only one component is left to vary: the actions of the human.
The level of risk created by the snag can be mitigated or exacerbated by the behavior of the individual. Injury and loss are more likely when the individual fails to attend to the known risks. When the individual is struck by the falling snag, the proximate cause is apparent, inattentiveness. It is not apparent, however, that this was an isolated case of inattentiveness. This inattentiveness might represent a general pattern of behavior that places the individual at risk in a variety of situations. To adequately respond to the accident, consideration must be given to both the proximate cause and the behavioral pattern. Unfortunately, traditional safety programs have placed far more emphasis on the former than on the latter.
Human Behavior and Accidents
Few will argue that most accidents and mishaps are directly related to unsafe behaviors. A review of the national air traffic control system revealed that 90% of the committed errors could be directly linked to human inattentiveness, poor judgment, or poor communications (Danaher, 1980). Mansdorf (1993) lists nine different causes of accidents and attributes all of them to human error in the form of inadequate training, supervision, and management. Given this consensus, the solution is simple; change the behavior where the accidents occur. Despite the intuitive appeal of this approach, efforts to increase safety in this manner often fail to produce the anticipated reductions in accidents. These failures occur because traditional safety programs generally focus on the unique circumstances and risks that, like the snag, remain relatively constant. Moreover, these programs often do not consider the broad spectrum of situations where the same behavior can also result in an accident.
A Training Proposal - A Training Proposal. By Wildland Fire Specialists. How to Base Actions on the Predicted Fire Behavior. We know the rule well but… Do we know how to be sure we can comply? All firefighters should be able to predict the changes in fire behavior. This is the course focusing on that objective. (Nov. 18, 2011)
Doug Campbell (RiP), Slide Serve, and Libitha. Excellent PowerPoint
Krause and Russell (1994) suggest that accidents result, not from unique circumstances or behaviors, but from the intentional display of risky common practice. (sic) These authors contend that an accident represents an unexpected result of an unsafe act that has become part of the working culture. Despite the best efforts to mandate safety, risky behaviors increasingly become acceptable practice each time they are performed without negative consequences. The process is similar to that seen in individuals who interact with hazardous products. Safety researchers have found an inverse relationship between safety behavior and familiarity (Goldhaber & deTurck, 1988). The probability that an individual will comply with safety guidelines decreases as familiarity with the product increases.
Wildland firefighters are not immune to this process. In response to the South Canyon fire of 1994, Rhoades (1994) writes, "And sometimes, even often, the risks we take in doing our jobs include violating the 10 Standard Fire Fighting Orders or ignoring the 18 Situations that Shout Watch Out." He further writes, "Nonetheless, very seldom does our inability to comply with the orders cause us to abandon our tasks..." Rhoades' statements reflect the fact that it is possible to violate standard safety practices without the worry of negative consequences. More importantly, however, Rhoades' comments suggest that the violations have occurred with such great regularity that they have become accepted practice in wildfire suppression.
Accident Prevention From a Behavioral Perspective
An effective prevention program begins by understanding that accidents often reflect the unfortunate outcome of hazardous acts that have become common practices and that these practices frequently span a multitude of different job tasks. To be effective, a safety program must: 1) identify the antecedent behaviors that result in accidents and near-miss incidents; 2) determine how frequently these behaviors occur; 3) evaluate training and management programs; 4) provide consistent and active feedback and reinforcement, and 5) develop remediation plans.
Identifying Antecedent Behaviors.
Traditional accident investigations tend to be very myopic, focusing only on the circumstances immediately involved in the accident. The purpose of an investigation is to identify the accident's cause with the aim of creating new procedures, equipment, and standards to eliminate or at least minimize the risk (Mansdorf, 1993). This investigative approach, however, must go beyond the traditional microscopic analysis to identify behaviors that are common in a variety of accidents. To facilitate the identification of these behaviors an investigation team should be composed of individuals from all levels of the workforce (Krause & Russell, 1994; Mansdorf, 1993). Moreover, efforts should be taken to reconstruct the accident with the aim of identifying the underlying behavioral patterns that might have precipitated it. Once identified the investigation needs to assess the extent to which these behaviors have been present in other incidents or accidents. Finally, the investigation must assess the degree to which the actions reflect the acceptance of hazardous and risky behavior as common practice.
Assessing the Frequency. To assess the frequency of unsafe acts, a system for reporting accidents, and near-miss accidents must be created. Near-misses play an important role in assessing the frequency of risky acts. From the behavioral perspective, near-misses represent accidents without the consequences (Krause & Russell, 1994). Moreover, given that unsafe behaviors infrequently result in accidents, near misses can provide better insight into employee safety. Mansdorf (1993) reports that for every serious industrial accident there are approximately 10 minor accidents, 30 property damage accidents, and 600 near-miss accidents.
The overarching motivation driving a reporting system should be the acquisition of reliable and valid data. To facilitate this process, the reporting system must encourage reporting from all levels of the workforce. Moreover, individuals should be instructed as to their reporting responsibilities. With regard to the logistics of the system, every reasonable effort should be taken to reduce the cost of complying with reporting requirements. These efforts might include simplifying reporting forms, the use [of] on-site or telephone based interviewers to whom unsafe acts can be reported, the use of anonymous data collection systems, the creation of safety surveys, the use of trained field observers, or the use of automated data collection systems. Such reporting programs might also guarantee immunity from disciplinary actions for individuals who report.
Evaluating Training and Management. There are a variety of questions that must be asked when evaluating training and management. Are instances of the desired behavior demonstrated during training? For example, fire shelter training has traditionally placed more emphasis on getting into the shelter than on other factors such as situational awareness, site evaluation, ground preparation, and contingencies all of which are essential to a successful shelter deployment. Are employees trained in the selection of the appropriate behavior? Invariably more than one option is available for each situation. In a situation where a burnover is inevitable, a firefighter can deploy a fire shelter or attempt to escape. Factors that influence this decision-making process must be considered in advance. Training should include techniques and procedures used to evaluate the various options. Is there a system to continue training apart from the classroom? On-the-job training (OJT) is a widely used technique but it suffers from many shortcomings. Trainers are frequently unaware of instructional techniques, training occurs only when time is made available, the situation typically dictates what skills are learned, and trainees often take a passive role merely watching and not demonstrating behavior (Gordon, 1994). Managers and supervisors must assess the extent to which training relies on OJT and develop specific programs to maximize its usefulness.
After training, are the behaviors practiced? Just as firefighters exercise to maintain a level of physical fitness, skills learned in training must be practiced to ensure competency. In a recent article on decision-making in the fire environment Braun and Latapie (1995) noted that training should include the rehearsal of behaviors that are needed in stressful conditions. Safety critical behaviors must be practiced until they become automatic. Finally, what is the perceived priority of safety? Do supervisors and managers expect safe behaviors? Are firefighters asked to work in high-risk conditions that are outside of safe parameters? Is there an established code of conduct that specifies the safe behaviors an individual is expected to display? Finally, is there an accountability system to which all firefighters are held? The answers to these and other questions provide an indication of the priority safety is given
Feedback and Reinforcement.
The concepts of training and reinforcement are closely related. At its most basic level, training serves to educate an individual about the various reinforcement contingencies (Anderson, 1995). That is, during training an individual learns the actions and behaviors that will be reinforced when training is complete. After training is complete, are the trained behaviors expected and reinforced? Moreover, have the trained behaviors been directly or indirectly extinguished by example or directive? For example, are firefighters more often reinforced for taking risks than for demonstrating good judgment?
While it is important to assess if trained behaviors have been reinforced, it is just as important to determine if unsafe behaviors have been inappropriately reinforced by environmental events. Although the ultimate goal of firefighting is fire suppression, a suppressed fire is not an appropriate reinforcer for firefighting behavior. This unsuitability stems from the fact that all fires eventually go out independent of the actions taken by firefighters. This inevitability makes fire suppression an indiscriminate reinforcer. That is, fire suppression could reinforce both safe and unsafe behaviors. Some would agree that factors such as weather often play a larger role in suppression than firefighters, but still argue that firefighters should be reinforced by the fact that the size of the fire has been limited. There might be some truth in this statement, however, it is not completely verifiable because firefighters often take advantage of areas where the fire would stop on its own (e.g., natural fuel breaks).
Care should be taken in determining the types of reinforcement and feedback individuals obtain from the environment. The containment and suppression of fires, the saving of structures and resources, and other similar events make poor reinforcers because they are indiscriminate and because they target the outcome of behavior and not the behavior itself. Efforts must be made to reinforce the safe behaviors independent of the outcomes.
Remediation Plans. Shortcomings in training, supervision, or management should not be viewed in isolation but as representative of a company-wide pattern of behaviors. Efforts to remediate these shortcomings must endeavor to address both the specific behaviors and the broader culture. Each plan should identify short-term and long-term objectives and the criteria against which the plan will be evaluated.
Programs aimed at enhancing safety by addressing the proximate cause of an accident only consider a small portion of the safety picture. Merely addressing the proximate cause fails to consider that the system either directly or indirectly trains, reinforces, and even expects employees to demonstrate hazardous behavior. An effective safety program must consider both the proximate cause and the working environment that promotes hazardous behavior. The program must identify unsafe behaviors and assess their prevalence. It must evaluate training to ensure that individuals not only gain the necessary skills but are provided with opportunities to exercise and practice those skills. The safety program must survey supervisors and managers to determine if skills learned in training are actively reinforced, and finally, it must make recommendations that affect behaviors and the system that supports them.
References - included within the link above in order to save space
Gary Klein PhD Naturalistic Decision Making and Wildland Firefighting
Gary Klein, Ph.D., is a Senior Scientist at MacroCognition LLC. Dr. Klein received his Ph.D. in experimental psychology from the University of Pittsburgh in 1969. He spent the first phase of his career in academia as an Assistant Professor of Psychology at Oakland University (1970-1974). The second phase was spent working for the government as a research psychologist for the U.S. Air Force (1974-1978). The third phase began in 1978 when he founded his own R&D company, Klein Associates, which grew to 37 people by the time it was acquired by Applied Research Associates (ARA) in 2005 Dr. Klein has developed several models of cognitive processes: A Recognition-Primed Decision (RPD) model to describe how people actually make decisions in natural settings; a Data/Frame model of sensemaking; a Management by Discovery model of planning to handle wicked problems; and a Triple-Path model of insight.MacroCognition LLC.
"The Recognition-Primed Decision Model [RPDM] describes what people actually do when they make difficult decisions. This has many implications for training and helping people make decisions under stressful situations. It can also help explain the factors behind bad decisions.
The standard method of decision-making is the rational choice model. Under this model, the decision-maker generates a range of options and a set of criteria for evaluating each option, assigns weights to the criteria, rates each option, and calculates which option is best. This is a general, comprehensive, and quantitative model which can be applied reliably to many situations. Unfortunately, this model is impractical. People making decisions under time pressure, such as fire fighters, don't have the time or information to generate options and the criteria to rate each option.
The rational choice model is also too general. It fits each situation vaguely, but no situation exactly. The worst news is that in studies in which people have been asked to follow the rational choice model exactly, the decisions they come up with have been worse than decisions they make when they simply use their own experience base. This model is of little value to training because it does not apply to most naturalistic settings or to how people actually make decisions when faced with complex situations under time pressure. Decision aids which have been produced to assist with the application of the rational choice model have been largely ineffective. Because of these drawbacks, a field emerged called Naturalistic Decision Making (see Table 1 [Figure 2.]). This field emerged because governmental sponsors such as NASA, FAA, the military, and others, realized that they had spent a lot of money and built decision models that did not work in the field. They wanted to get away from building analytical models which didn't work when they were brought into action. Naturalistic Decision Making uses expert decision-makers, and tries to find out what they actually go through in their decision-making process.
Figure 2. pros and cons bullet points discussed in his presentation Source: Klein
Instead of restricting decision-making to the "moment of choice," experts are asked about planning, situational awareness, and problem solving to find out how these all fit together. This model is used to understand how people face decisions in shifting and unclear situations and under high stakes. Team interactions and organizational constraints with high stakes are also used as factors. For years, researchers had been simply asking college sophomores what they would do given a set of options, and a clear goal. For Naturalistic Decision making research, experts are asked to size up actual situations, using all cues and constraints to set goals and make decisions.
The first study I performed to generate models and training recommendations for decision-making under pressure and certainty was a study for the Army. The Army Research Institute wanted some data on decision-making in real, stressful situations, and I thought that urban firefighters would be a good example of people who had become experts at making such decisions. We studied commanders who had about 20 years of experience, and studied the most difficult cases they had. Of the cases we studied, there was an average of five changes in the fire and in the way it had to be handled. About 80 percent of the decisions were made in less than a minute. As we started the study, we found that each expert firefighter told us that they had never made any decisions. They explained that they simply followed procedures. But as we listened, we realized that in each case, there was one option which they thought of quickly. They evaluated that one option, and if it seemed viable, they went ahead with it.
We began to wonder how they came up with that first option and how they were able to evaluate one option without others for comparison. The strategy used by the firefighters is the basis for the Recognition-Primed Decision (RPD) Model (see Figure 1 [Figure 2]). The first level consists of a simple match, where decision-makers experience a situation and match it to a typical situation with which they already have experience. Because of this, they know what to expect. They know what's going to happen, they know what the relevant cues are, what the plausible goals are, and a typical action. They are able to do all of this because of their experience base. Experience buys them the ability to size up a situation and know what is going on and how to react. That's what decision researchers weren't learning when they studied college sophomores who didn't have an experience base.
Figure 3. [Klein Figure 1.] —Recognition-Primed Decision model. Source: Klein
An example of the first level of the RPD model is a firefighter I interviewed early in the process. He explained to me that he never made decisions. After trying to press him on the issue, I asked him to describe the last fire he was in. He told a story of a fairly conventional fire. He described parking the truck, getting out his hoses, and going into the house. I asked him why he went into the house instead of simply working from outside, as I would have been tempted to do. He explained that he obviously had to go in because if he attached it from the outside, he would just spread it deeper inside the house. He took into account the nature of the fire, the distance of the house from other buildings, and the structure of the house. But, even while he was attending to these conditions, he never saw himself as making a decision. He never experienced that there was another option. He immediately saw what needed to be done and did it.
The second level of the model includes diagnosing the situation. On this level, expectancies are violated. The firefighter is trying to build a story to diagnose the event, and when evidence doesn't fit the story, the firefighter has to come up with a new scenario which fits the new evidence. There is still no comparing of options.
On the third level, decision-makers evaluate the course of action they have chosen. Originally, we weren't sure how people could evaluate single options if they had no other options to compare it to. As we looked through the materials we were getting, we found that a decision-maker would evaluate an option by playing it out in his/her head. If it worked, they would do it, if it didn't, they would modify it, and if modifications failed, they would throw it out. In the incidents we studied, commanders simply generated each option and then evaluated it for viability. Usually[,] the first option an experienced firefighter generated was a viable option, but they also understand that they should simply be satisfying, not optimizing. They will not necessarily pick the best option. They will pick the first one which is possible and involves minimal risk. The first viable option is chosen and improved upon, if necessary. It is not compared with all other options to see which one will be best. As soon as it is deemed viable, it is chosen and applied.
Naturalistic Decision-Making has implications for training. Decision training needs to teach people to deal with ambiguous, confusing situations, with time stress and conflicting information. Situation awareness, pattern matching, cue learning, and typical cases and anomalies can be taught by giving people a bigger experience base. Training could teach decision-makers how to construct effective mental models and time horizons and how to manage under conditions of uncertainty and time pressure.
Methods for providing better training include changes in such things as ways of designing training scenarios. Another strategy is to provide cognitive feedback within After-Action Reviews. This would do more than point out the mistakes which were made in an exercise. It would be an attempt to show decision-makers what went wrong with their size up, and why. Another method would include cognitive modeling and showing expert/novice contrasts. This would be done by allowing novice decision- makers to watch experts. Novice decision-makers would also benefit by learning about common decision failures. On-the-Job Training should be emphasized rather than simply assuming that once the traditional training is finished, decision-makers are ready to begin to function proficiently. Test and evaluation techniques and training device specification could also be improved. All of these might have an effect on the ability of firefighters to deal with stressful situations.
Why is it that people do make bad decisions? I looked through a database of decisions to identify reasons behind bad decisions. We came up with 25 decisions which were labeled as poor. Of those, three main reasons for bad decisions emerged. By far, the most prominent reason was lack of experience. A smaller number of poor decisions were due to a lack of timely information. The third factor was a de minimus explanation. In this situation, the decision-maker misinterprets the situation, all the information is available, but the decision-maker finds ways to explain each clue away, and persists in the mistaken belief.
The problem of lack of experience has many effects (see Figure 2 [Figure 3.]). Inexperienced decision-makers lack the understanding of situations to be able to see problems and judge the urgency of a situation, and properly judge the feasibility of a course of action. These are skills which could be developed to improve decision-making
Figure 4 - NDM factors that contribute and lead to poor decision outcomes. Source: Klein