Understanding farmer decision making and adoption behaviour

Author: Bill Long | Date: 07 Feb 2013

Bill Long 
Ag Consulting Co.

Take Home Messages:

  • We live by ‘rules of thumb’ and make decisions by ‘gut feel.’
  • Analysis feeds intuitive thought process
  • Differences in personality types affect decision making -  we don’t all think and learn the same way
  • There is logic behind ‘irrational’ decisions
  • Good communication is the key driver of successful farm business management
  • Think about how – rather than why – decisions are made

Introduction

An improved understanding of basic human psychology will assist those working in the farm advisory sector to help farm businesses to achieve their goals more effectively. Through an examination of the human factors that drive decision making processes, farm advisers can gain insights that will enable them to work more effectively with their clients, and to extend their understanding of an individual farm business as a whole.

Maximising profit is clearly not the only motivation for farmers. Farmers farm because they want to farm, because they enjoy the lifestyle and because they hold deep seated values and beliefs around living and working on a property that has often been in the family for generations. These personal goals, ambitions, values and beliefs often surpass rational economic decision-making processes in business management. Regardless of the quality of the land resource, technical experience, finance available and equity levels, a successful farm business can only operate effectively if the people running the business communicate well and have clearly defined business and personal goals.  Often, decisions that seem illogical and irrational to those not directly involved in farming family operations – for example, to purchase more land or over-capitalise on machinery – make perfect sense to those making the decision.

There is no doubt that good science and sound logical reasoning are essential in good decision making processes.  However, within this equation it is essential to note that for many, the drive and passion to achieve something at a personal and family level is often more powerful than reasoned logic that is based on financial optimisation.

This paper attempts to describe some of the human behavioural factors that influence human decision-making process and describes the influence of personality type on decision making. It also provides a view from a third party consultant working in the dairy industry on good farmer decision making process and finishes with a suggestion on ways to improve decision making at the farm level.

Does level of education affect analytical thinking process?

The level of tertiary education amongst the agricultural sector relative to the general Australian community is low. While education levels overall have improved over the last generation, it is clear tertiary education levels within the agricultural sector are lagging behind other sectors in Australia. An assumption might be that within the agricultural sector, the farm support industries (science, education, advisory) contain a larger proportion of tertiary educated personnel than those engaged in actual farming pursuits.

Does this mean farmers and advisers actually think differently?  If so, it may be argued that the development of skills in analytical thinking processes by farmers who have not undertaken university level training may take longer than for those who have undertaken training.  The science training undertaken by scientists and advisers to reduce impact of bias and emotion in decision making cannot be assumed to be at the forefront of thinking processes for those who have not undertaken such training.  Instead, there is emphasis on experiential learning in preference to science based approaches entailing more complete analysis of options through intensive data gathering and analysis.

Figure 1 .Relative proportions of the agricultural sector and the Australian community with tertiary qualifications, 1984-2009 (source Australian Bureau of Statistics, 2011)

Table 1 .Relative proportions of the agricultural sector and the Australian community with tertiary qualifications, 1984-2009 (source Australian Bureau of Statistics, 2011)

Decision making processes

The model shown below describes factors involved in decision making processes.  MCown (2010)  describes how analysis ‘feeds’ the intuitive thinking systems used by humans and also describes the preference of farmers to make decisions in response to certain stimulus based on experiential learning. This is described as an ‘if-then’ response – i.e. if it rains in late April, then I’ll sow a crop.

Diagram showing the decision making cycle.

Figure 2. How we make decisions model (Long 2011) (adapted from McCown)

 Developers of Decision Support Systems (DSS) often lament the fact their DSS are rarely used for decision making in the way in which they would like and describe the frustration of poor adoption and then disadoption of DSS by the farming sector. A common expectation of developers of DSS is that their models will be used by farmers (who, it is assumed, think the same way as they do) to simplify the decision process by processing all of the inputs required to make a decision, based on sound logic and reason. There is an expectation that once the analysis is complete and a number arrived at, then the decision is made. The assumption is that the ‘answer’ or ‘number’ as a result of the analysis bypasses the intuitive step in the decision process, thereby eliminating all the bias and human ‘emotional’ element of the decision. That is after all, the basis of rational, logical, scientific thinking.

When relating this model to education levels, perhaps non tertiary trained farmers with little experience do in fact ‘think differently’ to scientists or their advisers. The reality is very different, with most farm decisions being made in other ways and without the intervention of DSS. The model above identifies other considerations involved in making decisions, many of which are not based on rational economic theory.

Advisers report that they themselves are more likely to use the decision tools to learn about a topic. In a survey of twenty-seven consultants across South Australia and Victoria in 2010, discussion took place around who would use DSS. Statements like, ‘some (farmers) might play with them (DSS) when they have time, but are more likely to ring their consultant for an answer, ‘and ‘the use of DSS is the advisers job, that is what we are paid for’ along with statements such as ‘we shouldn’t be concerned that farmers aren’t using them as long as industry uses them’ were typical comments summarising consultant views on the use of DSS.

Furthermore, it is apparent that once the learning is complete, there is no longer a need to use the tool, hence dis-adoption of the tool occurs. Knowledge derived from the DSS is then transferred in general discussion between the advisers to the farmer in the context of the farming practices employed in the region.

Therefore, while many farm decisions are made under the influence of a DSS which provide learning on a topic, they are not necessarily used every time a decision is made.

Figure 2. Consultant response to the question, ‘Has the use of DSS improved your decision making process?

Figure 3. Consultant response to the question, ‘Has the use of DSS improved your decision making process?

Intuitive (‘gut feel’) decision making processes

So what is intuition?

Farmers frequently use intuitive decision-making processes in managing the farm business. Rickards (2009) describes ‘intuitive thinking’ as ‘a process by which our subconscious finds links between current situations and past experience and knowledge.’ Intuition allows us to make quicker decisions because it bypasses rational processes, but for decisions to be good, intuition depends on the quality of past experience and knowledge. Therefore, the more people (farmers/advisers) experience, read, discuss and think about a particular subject, the better their intuition. Despite having gaps in information, intuition enables a decision to be made.

Intuition is sometimes treated with scepticism as often the basis of the intuitive decision is difficult to substantiate or identify. Yet, in the agricultural domain at least, there is growing acceptance that intuitive thought processes are commonly used as the primary decision-making process by farmers. While the decisions made might not result in the optimal outcome, intuitive decisions are usually right if they ‘feel’ right. The term ‘feel right’ relates to the emotional component in the decision and if a decision ‘feels’ right, it not only satisfies the experiential learning but also satisfies the emotional drivers – the passion that lies within us to make the decision we make.

 Lehrer (2009) suggests that there is no universally correct solution to decision making. In comparing intuitive versus logical analytical reasoning  he suggests the either/or approach to the dichotomies is destructive and goes on to say that ‘natural selection has given us a brain that is enthusiastically pluralist’ and that sometimes we need to reason through our options and carefully analyse the possibilities and at other times listen to our emotions.

Lehrer (2009) says:

‘[i]t turns out we weren’t designed to be rational creatures. Instead, the mind is composed of a messy framework of different areas, many of which are involved in the production of emotion. Whenever someone makes a decision, the brain is awash in feeling, driven by inexplicable passions. Even when a person tries to be reasonable and restrained, these emotional impulses secretly influence judgement.’

Figure 3. Consultant responses to the question, ‘How did you make decisions without DSS?’

Figure 4. Consultant responses to the question, ‘How did you make decisions without DSS?’

In the consultant survey conducted in 2010, intuition (or gut feel) was mentioned most often as an important method used by advisers to make decisions. For those with many years experience, confidence in being able to draw on that knowledge from ‘somewhere in the subconscious’ is higher than for those starting out in industry.

Rules of thumb (heuristics) in decision making processes

The development and use of rules of thumb is very important within the decision making process. Rules of thumb are essential in decision making processes in that they simplify everyday decisions and thereby avoid sometimes complicated and time consuming analysis and information gathering. They guide everyday actions and are used in all aspects of business and personal decision making. However, they are not always right and can sometimes constrain and limit outcomes.

Simon (1957) proposed the theory of bounded rationality, which states that people are not always able to obtain all the information they would need to make the best possible decision. People experience limitations in formulating and solving complex problems and in processing information.

Rules of thumb provide very powerful platforms from which farmers and advisers are able to make decisions. Generalisations about an issue related to agronomy or financial management have served growers and their advisers well for years. Indeed, any researcher who hopes to communicate a message about their research outcome attempts to do so by drilling down to a few key messages from their research program, quite often as an abstract at the beginning of the paper. This kind of simplification is necessary in order to transfer findings into useable forms.

Figure 4. Consultant response to the question ‘How do non users (of DSS) benefit from DSS?

Figure 5. Consultant response to the question ‘How do non users (of DSS) benefit from DSS?

In the consultant survey conducted by the author of this paper, the development of rules of thumb as a result of using DSS was mentioned directly five times. Survey comments on extrapolation or modification might also be interpreted as some form of ‘rule of thumb’ development.

Stage of life (farming lifecycle) influence on decision making processes

People have different needs at different times in their lives. Howard (2009) reports that the needs of farming businesses are driven by the farmers’ own needs and goals in their lives. The following stages of a business/career lifecycle emerged from a series of interviews of Victorian farmers as part of a scoping study looking at the role of government service providers in farm business management. The phases and key goals, features and issues identified during these phases were:

  • starting out—gearing up
  • expanding income—young family
  • expanding income—succession of next generation
  • cruising along and
  • winding down

These phases of farming life reflect the different needs and desires of the people involved and their subsequent demands of the farm. Farmers at each stage have particular motivations that make them more/less inclined to focus on business management as an important aspect of their business operations. Therefore an understanding of these life stage needs is critical to understanding farmers’ business management needs. Clearly, the needs and timeframes of a farmer starting his career are different to those who are nearing the end of their career and subsequently, decisions made will differ.

Emotions in decision making processes

Studies of decision making processes emphasise rationality as the major function in the process. Mostly, the effects of anxiety, fear, frustration, doubt, happiness, excitement or similar emotions are downplayed or ignored. However, decisions are influenced by these emotions at a particular moment. Given the same objective data, people will make different choices when they are angry or stressed compared to when they are relaxed and calm (Robbins et al, 2001).

Robbins goes on to say that negative emotions can result in a limited search for new alternatives and a less vigilant use of information. Positive emotions, on the other hand, can increase problem solving abilities and result in a better extraction and use of information. People use emotions as well as rational and intuitive processes in making decisions. Failure to incorporate emotions into the study of decision making processes will result in an incomplete (and often inaccurate) view of the process.

Kahneman and Tversky’s prospect theory (1979) challenged traditional thinking that all investors make rational decisions.  Their research was summarised in the simple statement, ’[t]he pain of loss is twice as great as the pleasure of gain’. This was one of the first studies showing how much people disliked losses and, by extension, how much they would pay to avoid a loss. Furthermore, the research suggests investors hated the way a loss ‘makes them feel’ even more than the fear of loss itself. It seems the emotional impact of a loss, in particular the sense of regret that may accompany it, may have an equal or greater effect than the financial loss itself.

Examples of loss aversion theory being put into practice abound in cropping systems, manifesting in approaches to grain marketing and overuse of pesticides such as fungicides.

Stress effects in decision making processes

When people are affected by stress, their ability to think and rationalise is reduced. Psychologists tell us that the human brain is divided into two parts, the ‘ancestral’ mind and the ‘thinking’ mind. Abey and Ford (2008) report that the ‘ancestral mind governs basic emotions that prepare us to act.’ Emotions are there for a reason: they move us to make decisions. The ‘thinking’ mind is a rational, conscious mind that processes information into complex, abstract thoughts. It is involved in advanced cognitive activities such as reasoning, anticipation and planning as well as organising actions towards a goal.’

Under stress, people revert to using the ancestral mind to cope with basic functions. We tend to do things the way we have always done them. We tend not to want to take on board new information, or to think deeply about a topic or problem. Subsequently, we avoid attending meetings, field days and information sessions – essentially learning opportunities – and seemingly lose interest in making change occur. Therefore, when farmers are given advice when they are under stress of some sort, either financially or personally, they may ignore advice given and become more conservative in their approach to change. That is, they do things the way they have always done them and are unlikely to be persuaded to change practices regardless of the rational or economic justification. Change under these circumstances is likely to be very difficult and farmers will take a more traditional and conservative approach to farming operations during stressful periods.

Bias in decision making processes

Decisional bias is a common fault in decision making processes. Analytical approaches assist in limiting decisional bias, however many biases are commonly overlooked in many decision making approaches. Nuthall (2011) lists a range of biasing types, to which agricultural examples have been added for the purpose of this paper. These include:

  1. Anchoring – conclusions are altered or differ because of a different starting point (a discussion on previous high wheat prices influencing the price at which you are prepared to sell wheat in a ‘soft’ market).
  2. Selective abstraction – picking out evidence that suits (presentation of selected agricultural trial data to farmers is common).
  3. Conclusions without evidence (global warming will destroy farming in this area).
  4. Overgeneralisation – creating a hypothesis on limited information (the crop needs 100 kg of nitrogen every year based on results in the last two years alone).
  5. Dichotomous thinking – putting observations in two extreme categories rather than recognising what lies between (disease needs to be completely controlled or crop will be lost – when it may only result in a 5% yield loss).
  6. Availability effect (accessing easily obtainable information from the World Wide Web rather than researching through quality peer reviewed science papers).
  7. Primacy effect – remembering the first of the information provided.
  8. Recency effect – remembering the last of the information provided (last year’s yields are remembered but difficulty is experienced remembering the previous year).
  9. Halo effect – where something good is assumed to have several good attributes (eg. high yielding wheat also has good quality).
  10. Framing effect – where information is presented in a ‘positive’ fashion (95 % fat free versus 5% fat).

So far, this paper has touched on a number of factors that might influence decision making in some way. The previous points identify a range of factors influencing any individual at any time. The following section deals with the use of personality types as a way of generalising and grouping individuals, gives an example of another advisers opinion on good farm decision making as observed in the dairy industry and suggests possible ways in which farm decision making processes can be improved.

Influence of personality types on decision making processes

Creating frameworks to describe human behavioural patterns can be a useful way to anticipate individuals’ responses to situations. Understanding personality ‘types’ can help our understanding of likely behaviour and assist us in understanding our own and others’ strengths and weaknesses. Once some of these behavioural patterns are understood, we can tailor our approach to supplying and using information with particular individuals. There are many examples of personality type frameworks being used today to assist businesses in getting the most out of teams of people. Many frameworks are reasonably simple to understand with limited training and experience. An examination of personality traits as they exist amongst the farming community provides some guidelines that might help advisers deliver messages in a way that will influence decision making and fast-track adoption of new technology.

Strachan (2011) reports on one of the few attempts in Australia to define the rural culture using the Myers Briggs type indicator. The data source of this study came from 3000 farm managers and employees working in six major agricultural industries across Australia over a fifteen year period. During this study, the profiles of people working in the beef industry, cropping industries (including horticulture) and intensive industries (dairy, pig, and feedlot) were developed and compared with the Australian standard sample.

Table 1. Distribution of ‘temperaments’ in selected rural industries. Strachan (2011)

SJ SP NT NF
Beef 57% 25% 13% 5%
Cropping 52% 25% 17% 6%
Intensive 57% 22% 15% 5%
Australian sample 42% 13% 26% 18%

The’ SJ’ temperament (52%) describes a culture that is less likely to adopt new ideas and will resist change. Decision makers within ‘SJ’ temperament need to be convinced of the need to change. As a group, ‘SJ’ adults tend to define themselves by their experience and they have a deeper investment in its value. Unless there is a clear and desperate need to change ‘SJ’ types prefer to stick to set procedures, established routines and historic precedents to guide them and prefer practical, concrete problems rather than theoretical or abstract concepts involved in adoption of new ideas. The ideas need to be complete, packaged well, have the relative advantage for change clearly evident, be compatible with current practices and thinking simple to adopt  and with a short term return on investment obvious. They are the most risk adverse personality type.

The ‘SP’ types (25%) are impatient with abstraction and theories, often have a ‘do it now and fix the details later’ approach to problems and take a flexible and adaptable approach to organising their time. They don’t mind taking risks and like the ‘SJ’ group, like concrete problems and prefer guidelines, taking a step by step approach to problem solving and learning.

The ‘NT’ (17%) type strengths include problem solving and understanding complex systems. They enjoy pioneering almost anything and like to start new projects and may have trouble sustaining interest after the design phase. They value logic and knowledge. Intuitive (N) types are more likely to tackle new ideas –they are willing to ‘have a try’ at new technology without having the fine detail ‘packaged‘ for them. Often, attention to detail is simply overlooked. This may not be the most successful approach to long term business success as the ‘cost’ of new learning in farming can be extremely high. Being the ‘first’ to try new technology often results in mistakes being made along the journey resulting in crop damage and lower yields

The ‘NF’ (6%) types value authenticity, integrity and harmony – may see their life as one long search for meaning. They are great participatory decision makers – focusing on the people in the organisation. They have energy and enthusiasm for the things they believe in and can have a tendency to ignore problems in the hope they will go away. These types could be approached to organise group events and collaboration on new ideas. They engage well with others.

Recognising that we don’t all think the same way is the first important step in delivery of information. Just because we might like information presented one way, that doesn’t mean others have the same preference. We can modify our message delivery techniques to include all personality types and get our message across more quickly and effectively.

With approximately 80% of the farming population being ‘S’ types, it is of little surprise that new and innovative technology that might excite an ‘N’ type could take a while to be broadly adopted.  

Strachan (2011) goes on to say that

‘[a] common strategy has been for extension operators to collect and analyse data on, for example, farm production, costs and profit, and to extend this information to clients. The strategy assumes that farmers have identified the problems and needs. It also assumes that learning is a passive process of information transferred. Such a ‘directive’ approach to extension would be generally inappropriate for the rural ‘culture’ described above. This would be especially true for those engaged and animal industries, where traditional methods of animal management are too often part of a deeply held values system.’

Although these frameworks tend to categorise individuals as having certain behavioural traits, it is important to recognise that these traits or types are really ‘preferences’ to type. It does not mean that individuals can’t behave differently. By creating awareness of one’s preference to automatically react or behave in a particular way, we can train ourselves to deliver and respond in a different manner if desirable.

So how do farmers make decisions?

Farmers work in an environment where multiple variables with different risk profiles and complex interactions impact on their businesses (Gibb, 2009). Gibb reports that:

‘[g]ood farm managers appear to have a mysterious capacity to make ‘best bet’ decisions and implement them in a timely way. On closer analysis, they actually follow rules to achieve their success.’ Gibb suggests some of these rules are:

  • Identify the critical variables and don’t be distracted by non critical variables. Experience, observation and a comprehensive ‘world view’ contribute to identifying the key items quickly. Smart farmers listen to ‘experts’ but don’t follow them blindly because they know experts only ever see part of the ‘big picture’.
  • Act quickly and decisively. More often than not, the good options disappear quickly.
  • Make near ideal decisions rather than analyse a situation ‘to death’ and as a result, miss an opportunity that depended on getting the timing right.
  • Recognise that luck and timing are important to good outcomes that are largely outside of individual control.
    • Being passionate about what they do provides resilience in adverse conditions.

Gibb argues that management skill comes down to the ability to make good decisions in a timely manner. ‘Due to the unpredictable nature of the environment in which farmers work, it is impossible to make the best/most profitable decisions all the time. A decision that turns out as such is therefore a ‘best-bet’ decision with the wisdom of hindsight, and cannot be planned for with such a high degree of accuracy owing to the unknowns.’

Farm Advisory Boards - A way forward?

Most large businesses across the world use a regular formal meeting process to assist in strategic business management and development. Few family farms do this. Businesses set up as companies require directors who by law are required to formally meet in order to manage the business. Small farm businesses operate under many legal structures and have regular production discussions with a cropping adviser or a financial adviser such as an accountant. These meetings are often separate and may involve different members of the farming family business.

Often, meetings involving all members of the business are held in times of crisis, such as a looming succession issue or financial pressure caused by drought or a major purchase decision such as the farm next door coming on the market.  Making decisions under such pressures can be stressful.

Board meetings provide a structured, disciplined platform to deal with the myriad of production, financial and personal factors that need to be considered in running any business. They provide a regular opportunity for communication between all business partners and for sharing of visions and goals as well as planning for the future.

Successful boards utilise independent chairs with the skills to facilitate discussion in a way that includes all parties in discussion. An effective chair should have a good understanding of decision making processes and be able to weed out the influence of bias and prejudice in decision making processes. They might also bring other skills that are important to the business such as finance, production or human resource management skills that will assist driving the business forward. An understanding of the personality types of the people involved in the board (mostly family members in farm business) is also useful as this provides an opportunity to recognise differences in the behaviour of individuals, thereby creating an opening to both recognise and exploit each others’ strengths in order to move forward. Facilitation and interpersonal skills are more important than good accounting or agronomy skills for this task. These are skills that can be learned relatively quickly and developed with practice.

Just as farmers invest in the hardware (machinery) to grow the crops and service it well before busy periods, it is equally important to invest in and service the human resources that actually run the business. Faulty decision making is as damaging to a farm business as faulty and dysfunctional equipment. Investment in personality type profiling for family and business support members is a fulfilling and enlightening experience and can improve communications considerably.

Building skills in, or employing those with the skills, to use decision support systems to assist in analytical thinking  can provide opportunities to explore a range of ‘what –if’ scenarios. Exploring the financial impact of a run of dry seasons, or a run of good seasons provides an opportunity to plan response strategies in advance and without the stress. This allows time to think through how we might react if that situation was to occur in real life outside of stressful times, so that when such a situation occurs in reality, our response is considered and more automatic (and hence less stressful.)

Summary

Understanding the human decision making process is important if we want to assist our farmer clients in achieving goals. There is no one ‘right’ recipe, ‘right’ delivery style or ‘right’ formula for every farm business.  Individuals within farm businesses (father and son, siblings, husband and wife teams) have different ambitions which may at times, be in conflict. Stage of life in the farming lifecycle, personality type, stress levels, entrenched values and beliefs and emotions are just some of the fundamental human elements that influence decision making processes on-farm. Consideration of these factors is essential if farm businesses are to progress. Failure to account for these factors will most likely result in personal conflict which can lead to significant change and in some cases, business failure.  Understanding these human elements will help us understand the reasons behind some of the decisions that are made that might occasionally contradict the advice given by industry support personnel.  A better understanding of the decision making process will help deliver information in a more effective manner, speed adoption processes and improve communication, which will result in better outcomes for agricultural business owners.

References:

Abey A, Ford  A 2008, How Much is Enough? Dennis Jones and Associates, Victoria

Briggs Myers, I 1980, Gifts Differing, Understanding Personality Type, Davies –Black Publishing, Mountain View, California

Gibb, I 2009, How do some farm managers always seem to make the right decision? in Flanagan-Smith, C, Making it practical, Discussion paper for Birchip Cropping Group.

Howard, K,2009 (pers. com)

Kahneman, D. and A. Tversky 1979. Prospect Theory: An Analysis of Decision Making under Risk, Econometrica 47: 263-91.

Lehrer, J 2009, How We Decide, Mariner Books Houghton Mifflin Hardcourt, New York

Long, W 2009, People Factors Driving Farm Decisions or A Bit of Bush Psychology, Grains Research Update, Adelaide, GRDC and Jon Lamb Communications, St Peters, South Australia

Long, W. and Cooper, I 2011, Farmer Decision Making in Rainfed Farming systems – The role of Consultants, Farming systems Groups and Decision Support Systems in Australia. Chapter 37, In: Tow, P., Cooper, I., Partridge, I., Birch, C. (eds)   Rainfed Farming Systems, Springer

Long, W. 2012,  The Logic behind Irrational Decisions, Grains Research and Development Corporation – Farm Business Update, Adelaide , ORM Communications, Bendigo, Vic.

McCown, R. (2010) Reinventing model based decision support with Australian dryland farmers: 5. Cognitive and social theory to inform analytical intervention in intuitive practice

Nuthall, P.L., The Psychology of Decision Making in Farm Management., Farm Management Group, Lincoln University, Canterbury (unpublished)

Rickards, L 2009, Uncertainty, Complex Risk, Vulnerability, Resilience and Adaptation. GRDC adaptive management forum Melbourne,

Robbins, S, Millet, B, Cacioppe, R and Waters Marsh, T, 2001 Organisational Behaviour, Leading and Managing in Australia and New Zealand, (3rd Edition), Pearson Education Australia Pty Ltd.

Simon, H.A 1955, A behavioral model of rational choice, Quarterly Journal of Economics 69: 99-118.

Strachan, R, 2011, Meyers Briggs Type Indicator Preferences by Industry and Implications for Extension. Pgs171-174 In Jennings, J., Packham.R.,Woodside.D., (eds) Shaping Change: Natural Resource Management, Agriculture and the Role of Extension

Contact details

Bill Long

bill@agconsulting.com.au

www.agconsulting.com.au

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