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COLLECTIVE : , MEMORY, AND COMMUNITY

Abigail V. Aldis

TC 660H Plan II Honors Program The University of Texas at Austin

May 5, 2020

______Dr. Jarrod Lewis-Peacock Departments of and Supervising Professor

______Dr. Judith Coffin Department of History Second Reader

ABSTRACT Author: Abigail V. Aldis Title: memory: history, memory, and community Supervising Professor: Dr. Jarrod Lewis-Peacock

Memory, defined as a representation of the past, is at the core of what it is to be human. Memory of the defines a person’s , because when we remember, we remember ourselves. Memory ranges from holding in our brain for a few seconds to storing information for an entire lifetime, from memory of the immediate past to childhood to memory of events only experienced through second-hand storytelling. Memory is an individual phenomenon, but it is inherently collaborative. People do not physically share memories; memories are held in the of individuals. However, memories are shared, reinforced, altered, and forgotten largely through conversational interactions. Shared memories define what it means to be a community. Through conversation and societal structures, memories become collective in communities. Thus far, has largely been studied in a fragmented way, which I argue is detrimental to the field and to real-world applications. There have been two main approaches to collective memory: one is the psychological approach, and the other is the sociological approach. These approaches both have important components but leave other essential components out of the discussion. I argue that the best approach to studying collective memory and other collective phenomena is the social-interactionist approach, which starts with relevant cognitive phenomena, looks at how those cognitive phenomena are modified in social settings, and studies how the phenomena propagate across large social networks. I argue for an extension of this approach to include societal context variables such as educational standards and norms within communities because those factors also have large influence on the collective memory of a community. This thesis first gives a review of relevant cognitive processes, then moves to a discussion of the study of collective memory. I use a case study to demonstrate a modified, qualitative version of the social-interactionist approach to collective memory, then conclude with a discussion of the possibilities for real-world solutions using this method.

Acknowledgements: I am extremely grateful to Dr. Lewis-Peacock and Dr. Coffin for working with me and coaching me through the writing of this thesis. They pushed me, encouraged me, and gave me new perspectives. Thank you for sticking with me through this process.

2 Table of Contents

Abstract…………………………………………………………………2

Part I: Individual Cognitive Phenomena………………………………..4

Early Memory Studies……………………………………………………………………………4

Types of Individual Memory……………………………………………………………………..6

Models of Individual Memory……………………………………………………………………6

Problems with Individual Memory………………………………………………………………13

Summary…………………………………………………………………………………………17

Part II: Collective Memory…………………………………………….18

Background on Collective Memory……………………………………………………...………18

The Two of Collective Memory……………………………………………………..…22

Social-Interactionist Approaches……….…………………..………………………………...….25

Part III: Case Study…….……….……………………….……………..33

Southern Civil War Memories: Generational Shifts and False Memories………………………33

Part IV: Implications of Collective Memory Studies………………….35

References……………………………………………………………...42

Biography………………………………………………………………49

3 Part I: Individual Cognitive Phenomena

Oftentimes when observing group or sociological phenomena, one notices that a process that happens on a cellular level or on an individual organism’s level can be generalized to much larger social processes. For example, in his essay Social Behavior as Exchange, George Homans discusses "dynamics of exchange" that "generate the static thing we call 'group structure'"

(Homans, 1958, p. 606). The material and immaterial things exchanged between people eventually create a state of equilibrium that is the group structure. A very similar process can also be observed on the cellular level. In neurons, ions cross back and forth across the cell membrane, creating an electrochemical gradient. This dynamic movement creates a resting membrane potential that stays relatively static until an action potential comes along. The ions are always moving back and forth, but an equilibrium state exists simultaneously. In this thesis I argue that another example of individual-level phenomena that can inform broader group patterns is individual memory. To follow a social-interactionist approach to studying collective memory, we first must understand the individual-level cognitive phenomena; only then can we investigate the way memory becomes collective in social networks.

This section gives a brief overview of the scientific study of memory, guided by Michael

Jacob Kahana’s book Foundations of Human Memory. This book gives an excellent overview of memory of events experienced in a specific context, or , which is the type of memory relevant to our study of the way historical memory becomes collective in communities.

Early Memory Studies

Memory has been studied since ancient . Aristotle thought deeply about memory and conceptualized it in terms of associations. Association is the phenomenon in which thinking

4 of one thing leads to thinking of another thing. In other words, if two events are related, they consistently occur at the same in our thoughts. Aristotle said that two things are generally associated when the two things have similar or opposite meanings, such as the of hot and cold, or were learned in the same context (Aristotle, De Memoria et Reministia). In the simplest terms, context is the place, time, or situation in which learning occurs. The of associations will be central to our discussion of both individual and collective memory.

The scientific study of memory began in 1885 with ’ work On

Memory (Kahana, 2014). Ebbinghaus wanted to study memory and associations experimentally and created methods for doing so. The of remote associations developed from

Ebbinghaus’ work, which states that associations are strongest between items close together in time and become progressively weaker for items that are further separated in time (Ebbinghaus,

1885). After Ebbinghaus laid the groundwork for experimental study of memory, many laboratories began studying memory. These early labs mainly studied “the rate at which performance improves with practice,” “the rate at which performance declines with disuse or interfering activity,” and “the ways in which different factors influence the rates of learning and ” (Kahana, 2014, p. 9). Müller studied associative learning and developed the concept of interference, which is the that forgetting is actually the interference of newer learning with previous learning (Müller, 1900). There are actually two types of interference: proactive interference and retroactive interference. Those concepts will be discussed more in detail later in this section.

5 Types of Individual Memory

There are many types of memory that are often studied in different ways. The main division in memory types is between short-term and long-term memory. Short-term memory is often called because it is memory for information that a person is immediately aware of. An example of working memory is remembering a phone number that someone just told you. On the other hand, long-term memory is held in the brain for longer than the immediate present. Long-term memory is divided into explicit and ; memories are conscious in and unconscious in implicit. An example of implicit memory is a person’s ability to remember how to perform a skill such as riding a bike. Explicit memory is conscious memory for and events, also known as declarative memory. The focus of this thesis is declarative memory, which can be divided into episodic memory, which is memory of events and experiences, and , memory of facts and concepts. The term episodic memory was coined in 1972 by and defined as “the form of memory that allows us to associate the many different types of information constituting an event into a spatio- temporal context and to later use the content of the event to retrieve its context” (Tulving, 1972, p. 385). It is important to remember that episodic memory does not represent an objective account of an event. Episodic memory represents an individual person’s subjective experience; the memory is part of a person’s timeline. When an episodic memory is retrieved, it is a kind of time travel; in remembering something, one remembers oneself.

Models of Individual Memory

There is a wide array of methods used to study declarative memory and a wide variety of theories about how sensory information is represented, stored, and retrieved in memory. There is

6 no unified or comprehensive theory for memory, but decades of experimental research lend some insights into how the human memory system works. We will focus on attribute and neural network models of memory. Attributes are the various factors contributing to a memory; the information that makes up a single memory is “distributed over multiple attributes, features, elements, or dimensions” (Kahana, 2014, p. 85). Stimuli are represented in the brain by electrical activity of neurons, and “the firing rate of each neuron can be thought of as representing the along the attribute coded by that particular cell” (Kahana, 2014, 85). In attribute models, memories are thought of as a pattern of varying degrees of neural activation. The representation of the memory is distributed throughout an array of neurons and is often called a memory trace or the engram. This means that a memory is not stored in the brain in one distinct spot but scattered in a pattern of activation.

Memories are distributed across a wide array of neurons, but we know that the , medial temporal lobe, frontal cortex, and parietal cortex are important to memory function. Certain types of neurons respond more strongly to specific types of stimuli and therefore a bigger part in a certain attribute of a memory. For example, place cells in the hippocampus increase their firing rates in specific locations in space and provide a context- dependent map of one’s surroundings (Ekstrom et al, 2003), while pair-coding neurons in the medial temporal lobe have been shown to represent paired associates (Sakai & Miyashita, 1991).

The different attributes do not contribute to a memory equally; some attributes are learned better than others. For example, if I am remembering a person I met yesterday, I might remember where I met them really well, but remember what time it was more vaguely. I might remember that they had brown hair, but not remember the exact words that we spoke to each other. Again,

7 those different dimensions are distributed throughout different types of neurons and brain regions in varying degrees of strength.

What happens if the same stimulus is presented on different occasions? For example, if I heard the word chocolate when I was watching the movie “Charlie and the Chocolate Factory” as an 8-year-old then I heard the word chocolate again on Valentine’s Day as a 17-year-old, what would the representation of the stimuli chocolate be like in my brain? The word chocolate in these two cases is presented in completely different situations and times of life. There are two hypotheses for explaining this situation, the multiple trace hypothesis and the unitrace hypothesis. The multiple trace hypothesis states that every time a stimulus is presented (or a memory of that stimulus is retrieved), the stimulus is re-encoded, leaving a new memory trace

(Moscovitch et al, 2006). The multiple trace theory also states that “the hippocampus is needed for re-experiencing detailed episodic and spatial memories no how old they are''

(Moscovitch et al, 2006, p. 179). The unitrace theory states that stimuli/events and their associations are all stored in a single memory vector; when the stimulus is presented again, the new information is added to a composite representation (Murdock, 1982). Both models assume that the end result is a kind of summation of the various instances that a certain stimulus has been experienced, whether the memories were stored in one trace or in multiple traces. One experience might have evoked stronger activation than another, so that experience will likely have a larger effect in the summation.

One major type of association models is neural-network models. In neural-network models, neurons are referred to as nodes, and it is assumed that every neuron is connecting to many other neurons, producing a highly interconnected network of nodes. Each neuron, or node, has an activation value, and each connection has a strength value, or weight. Activation values

8 can be thought of as being either above or below its normal, or average, activation level. Weights show the strength of the synaptic connections between nodes. The vector of activations for the neural network is called the state vector, and it is constantly changing depending on what we are thinking about at that moment or with new information (Kahana, 2014). Each node in the network gets information from other nodes and sends information to other nodes. Donald Hebb’s view of learning, known as Hebbian learning, can be applied to these models. Hebbian learning is the idea that learning happens when there are changes in the strengths, or weights, of connections between neurons (Hebb, 1949). If we prescribe to Hebb’s idea of learning, changes in memory are also the result of changes in the strengths of connections between neurons in the memory trace.

Norman and O’Reilly present a neural-network model that focuses on the role of the hippocampus and the medial temporal lobe cortex in memory. In their model, the hippocampus and the medial temporal lobe cortex act as complementary learning systems. The medial temporal lobe cortex is “specialized for slowly learning about the statistical regularities of the environment” and “assigns similar representations to similar stimuli,” while the hippocampus

“assigns distinct representations to stimuli,” allowing it to learn faster without huge amounts of interference (Norman & O’Reilly, 2003, p. 613). The cortex supports familiarity judgments, while the hippocampus supports of earlier stimuli.

So far, we have seen that memories are distributed in the brain throughout a network of neurons to form a memory trace. The network of associations in Aristotle’s view were links between two distinct items (Kahana, 2014), but there is a more complex view of associations in which they do not have direction but are new representations that combine parts of the memory unit (Asch & Ebanholtz, 1962). In other words, associative learning is not a matter of forming

9 and strengthening simple links; it is a complex process in which people try to relate and anchor new information to existing . If associations are multi-directional and complex, then memories are combined and intertwined in an endlessly complex fabric of connections that, importantly, depend on a person’s previous state of knowledge.

During the 1970s, the idea that long-term and short-term memory are separate processes became popular (Kahana, 2014). However, there is debate over whether the two types of memory are in two distinct processes. One of the most influential variants of the neural- network models is the SAM (Search of Associative Memory) model, a dual-store model proposed by Atkinson and Shiffrin. The SAM model accounts for long-term and short-term memory as distinct but interacting processes. There are two types of in SAM, short-term store (STS) and long-term store (LTS). STS acts as a memory buffer in which there is a limited capacity for immediate information. Information in STS can be immediately recalled. Since STS has limited capacity, as new items enter STS, older items drop out. Also, the longer an item stays in SAM, the item to context association grows stronger, and the longer two items are in STS together, the item to item association grows stronger. LTS acts as a matrix, much like the neural- network models, of strengths of associations between items and between items and context

(Atkinson & Shiffrin, 1968). The SAM model has been refined and updated over the years. A few of these updates include allowing context to evolve gradually and the incorporation of semantic similarity effects (Sirotin et al, 2005). To include semantic similarity effects, or associations between items based on their meaning that could exist prior to an experiment, LTS is divided into two parts. One part simulates episodic LTS, or associations based on context, and the other part simulates semantic LTS (Sirotin et al, 2005).

10 STS holds recent items that are being studied, and as STS reaches capacity, older items drop out to make space for newer items. Rehearsal in STS strengthens associations in LTS. To retrieve information, items in STS are available for immediate , but items in LTS require a two-phase process. First, an item is sampled, with context used as a retrieval cue. An item is more likely to be sampled if there is a strong association between context and the item.

After an item is sampled, it may or may not be recalled. Again, the stronger the association between the item and the context is, the more likely the item will be recalled (Atkinson &

Shiffrin, 1968). Also, the likelihood that an item will be sampled and recalled depends on the distance between the learning context and the recall context (Sirotin et al, 2005). Semantic, episodic, and contextual information work together to predict sampling and recall in a multiplicative fashion such that episodic and contextual associations inhibit semantic associations and versa. This multiplicative rule ensures that semantic associations will not overwhelm the memory trace with semantic interference (Kahana, 2014).

The SAM dual-store model is very successful at predicting many aspects of free recall data, including “recency effects, primacy effects, the contiguity effect and the semantic- proximity effect, prior-list and extralist intrusions, and the effects of semantic organization on learning across multiple trials” (Kahana, 2014, p. 238), but there are some data that do not fit well with dual-store models. Dual-store models do not account for “the fact that recency depends on the relative (rather than the absolute) time since an item was studied” (Kahana, 2014, p. 242).

SAM assumes that recency effects, or the higher probability of recently learned items to be recalled, depend on the size of STS and the rate of displacement of items from STS. However, data show long-term recency even with continuous distractors during learning (Bjork & Whitten,

11 1974). Due to this contradiction, single-store models such as the temporal context model (TCM) arose.

The temporal context model (TCM) proposes that “retrieval of prior contextual states” drives contextual drift (Howard & Kahana, 2002, p. 269). In the TCM, recency is due to the greater strength of the context-item association for recently studied items. Since context changes throughout learning, the items learned last will have the strongest association to the context of the recall attempt. Contiguity arises from the fact that recalling an item also recalls its context, which then cues recall of neighboring items. These associations are stored in a neural network, with one of connections representing item-to-context associations and another set of connections representing context-to-item associations (Kahana, 2014). The SAM and TCM models are different, but both show that context and context retrieval have an important role in free recall.

There have been studies performed to search for neural correlates of both memory search and contextual reinstatement. One study tested whether brain activity during retrieval of an item from memory matches brain activity during storage of that item. Using functional magnetic resonance imaging (fMRI), researchers found category-specific brain activity during item study and found the same pattern of category-specific activity immediately before recall of that same item (Polyn et al, 2005). In another study, electroencephalographic

(EEG) activity was measured. They found the same pattern of high-frequency gamma activity during item study and during recall of the correctly recalled items. For incorrectly recalled items, the EEG activity did not match (Sederberg et al, 2007). In another study, individual neurons were identified as increasing their firing rate for certain items, significantly in hippocampal and other medial temporal lobe regions (Gelbard-Sagiv et al, 2008). We have already seen in this paper

12 that contextual reinstatement is important to recall and is “a hallmark of episodic, or event-based, memory” (Kahana, 2014, p. 264). Using electrocorticographic (ECoG) activity, researchers tested whether contextual reinstatement can be observed in brain signals during episodic recall.

They found that the brain activity recorded during item recall was similar to brain activity both during study of the item and during study of neighboring items. Similarity between brain activity decreased with distance between items, which also represents distance between context

(Manning et al, 2011). These studies provide neural for reactivation of brain activity patterns both during recall and study of an item and during contextual reinstatement.

Problems with Individual Memory

At the beginning of this section, I mentioned interference and its two types, proactive and retroactive. We can think of interference as the insertion of conflicting associations. Interference can go both ways; new learning can get in the way of old learning and old learning can get in the way of new learning (Underwood, 1957). Retroactive interference is when new, conflicting information gets in the way of recalling old information. Proactive interference is when earlier learning gets in the way of new learning. Context and changing context play a role in interference. Context functions to “focus retrieval on the appropriate associations, thus limiting competition from other associations,” like we saw in the TCM model (Kahana, 2014, p. 133).

Proactive interference goes hand-in-hand with the view of associative learning as a complex process in which people try to relate and anchor new information to existing knowledge. If a memory trace about a certain topic already exists in a brain, new associated information will be added to that trace. There will not be a pure, objective representation of the new learning because there is already existing knowledge that will now exist in summation with

13 the new knowledge. Another dimension of proactive interference is contextual change. In the case of changing context, memories from earlier experiences often supersede later ones, especially when there is a long delay between the experiences (Postman & Keppel, 1977).

However, interference works in both directions. Retroactive interference, when new conflicting information gets in the way of recalling old information, shows response competition in a similar way to proactive interference but also displays another process called unlearning

(Kahana, 2014). Even in experiments controlled for response competition, there was still substantial retroactive interference shown. This finding led to the specific unlearning hypothesis, which proposes that learning inhibits the attributes of competing associations (Anderson &

Spellman, 1995; Anderson, 2003). If someone learns an A-B list then learns a second list A-C, as the learning of A-C gets stronger, there is inhibition of memory of the A-B pairs and attributes of

B itself. As someone gets better at recalling C, they get worse at recalling B and vice versa

(Anderson & Spellman, 1995). Anderson and Spellman’s findings slightly redefined retroactive interference as unlearning through inhibition. Unlearning is a process that is crucial to memory studies. Memory and forgetting go hand in hand. The specific unlearning hypothesis suggests that forgetting comes not from memories simply decaying over time but from interference and inhibition among memories (Kahana, 2014). When we expand our discussion of memory to collective memories, we will see that both retroactive and proactive interference effect generational differences in memory and how individuals and groups of people can “change their ” over time.

In addition, the selective retrieval of memories causes reinforcing and suppression effects. While recalling an item reinforces it in memory and increases the likelihood it will be recalled again, if other items associated with the same cue are not recalled, the likelihood

14 increases that those items will be forgotten. There are three assumptions underlying this strength- dependent competition model of interference: first, that items with the same cue compete for conscious recall during retrieval; second, that the recall of one item will decrease as the recall strength of another related item increases; and third, that retrieval is a learning event in itself.

These two opposing phenomena are called reinforcement and retrieval-induced forgetting.

Reinforcement occurs when, during retrieval of a previously learned item, an item is recalled.

Reinforcement strength increases with repeated recall of the item. On the other hand, retrieval- induced forgetting occurs when an item that is associated with or shares a cue with a recalled item is not recalled. Actually, the more strongly the non-recalled item is associated to the recalled item, the stronger the forgetting effect (Anderson et al., 1994). For example, suppose you attend a lecture that informs you about the basic behavior of cats. The lecturer explains that domestic cats generally use litter boxes and clean themselves daily. After you leave the lecture, your friend tells you that she has decided to change her major to history. The litter box item and the cleaning item are strongly associated; you learned the items in the same context and they both refer to cat behavior. The history major item is unrelated to the items about cat behavior.

The next day, suppose someone asks you what you learned in the cat behavior lecture. You say that you learned that cats use litter boxes. You do not mention the cleaning item. The next time someone asks you what you learned in the cat lecture or you individually try to recall what you learned, you will be more likely to recall the litter box item, and less likely to recall the cleaning item than the first time you recalled the information. If you do not recall the history major item, there is no effect on the likelihood of recall because it is loosely associated with the items learned in the cat behavior lecture.

15 Another phenomenon of is , or “mistaken memory for an event that never occurred or that occurred but not as remembered” (Kahana, 2014, p. 209).

People are often very confident that the incorrectly recalled item is correct and was on the study list. A popular technique for studying false memory is the Deese-Roediger-McDermott (DRM) procedure. In the DRM procedure, people study a list of words that are semantically associated with a word, the critical word, that does not appear on the studied list. Participants will often recall the critical word that is related to the list words even though the critical word did not appear on the list (Roediger & McDermott, 1995). Intrusions of the critical word appear frequently in the DRM procedure. Intrusions of other words such as pre-list intrusions and extra- list intrusions appear, but much less frequently than the critical word (Kimball et al, 2007). There are two dominant theories explaining false memory: the activation monitoring theory and the fuzzy trace theory. The activation monitoring theory posits that studying a word activates semantically associated words in memory, and because the critical word is semantically associated with the studied words, the critical word becomes strongly activated (Roediger et al,

2001). The fuzzy trace theory posits that accessing the semantic attributes of the item promotes a false memory of the critical word, and that accessing the contextual attributes of the item promotes correct recall of the studied list. However, the semantic attributes are assumed to be stronger than the contextual ones (Brainerd & Reyna, 2005). The studies done on false memories are on a much smaller time scale than what is helpful for our discussion of historical memory, but “many that govern recall of lists operate at multiple time scales” (Kahana, 2014, p.

219). For example, if someone is asked to recall all of the films they have seen, they will list films that they and have seen often (reinforced often in long-term store/neural-network), films they have seen recently (recency effect), and maybe even list some films that their friend

16 was talking about that they have not actually seen (false memory intrusion). This example shows the generalizability of cognitive memory phenomena and their ability to operate at time scales much larger than what is studied in laboratory situations.

Part I Summary and Conclusion

The experimental study of memory has shown that memory is complex and varied.

Memories are encoded, stored, retrieved, and sometimes forgotten. They are stored in some sort of network of neurons with various strengths of connections, and the same brain activity that occurs during of a memory also occurs during retrieval. Furthermore, the concept of associations, represented by connections between neurons, is crucial to understanding memory.

A stimulus or event is associated with other things in both a semantic and episodic manner. Items are associated semantically if they have similar meanings or are related; items are associated episodically if they occurred in the same or similar contexts. There are many models for memory, but all assume that memories are stored across a network of neurons and that the memory trace is added to when new associated stimuli are presented. Finally, memory is imperfect; false memories, interference, and retrieval-induced forgetting are examples of this imperfection. While the experimental study of individual memory is on a relatively small time scale, the same principles found in list recall experiments largely apply to memory on a larger time scale, so this information is very relevant to our discussion of historical and collective memory. We have a basis in the individual-level cognitive phenomena; we now move to the collective.

17 Part II: Collective Memory

Background on Collective Memory

The study of memory and collective memory is often fragmented and defined more in terms of the topic of inquiry; someone may study memory of the Holocaust, memory of the

American , , or repressed memories. There is a need to bring together the field of memory studies, specifically collective memory studies. The backbone of the field is the definition of memory as the various “ways in which people construct a of the past” (Confino, 1997, pp. 1386). Following from Confino’s definition of memory, a broad definition of collective memory is: representations of the past shared within a community. This basic definition seems simple enough, but there has been much discord about how to define and study collective memory.

Before the scientific study of individual memory began, philosophers and great thinkers were still thinking about memory. For example, Plato and Aristotle both thought about memory.

They did not consider the question of who remembered to be of great importance; rather, they considered the question of what it means to have or to search for a memory. Furthermore, the solipsism of many of the great philosophers, or the view that the self is all that can be known to exist, led to a school of inwardness concerning memory. Three examples of thinkers in that school of inwardness are Aristotle, Locke, and Husserl (Ricoeur, 2004). Aristotle said that memories are a private possession and that the memories of one person cannot be transferred into the memory of another person. Aristotle also said that memory is of the past, and the past is composed of an individual’s impressions. Memory gives people a means to move through time, while at the same time the impressions of the past are what “assures the temporal continuity of the person;” in other words, Aristotle was saying that memory assures one’s identity as a person

18 (Ricoeur, 2004, p. 96). In remembering something, one remembers oneself. John Locke argued that alone makes personal identity, and consciousness and memory can be defined as being one in the same. Husserl argued that memory is a unique form of consciousness. He refers to memory as the “flow of consciousness” that has inherent unity across phases (Ricoeur,

2004, p. 110).

These early discussions of memory, with their inward focus, do not sufficiently focus on the social aspects of memory. One of the first scholars to talk about a collective present in was Emile Durkheim. Before the term collective memory was established, Emile Durkheim discussed in his work The Elementary Forms of Religious Life.

Durkheim asserts that “society is a sui generis; it has its own peculiar characteristics” and that you cannot derive “the whole from the part, the complex from the simple” (Durkheim, 1912, p. 29). He is saying that society provides an external structure that defines how people live and conceptualize their reality. Society is something more than the sum of individual and actions; society is the umbrella over everyone. Much like consciousness from a Cartesian dualist’s perspective, collective consciousness in Durkheim’s view is derived from a slightly mystical force. Durkheim’s view of collective consciousness is difficult to trace because of the abstract of the collective consciousness; you cannot simply add up individual actions and produce the collective. Durkheim says that “collective representations are the result of immense cooperation…to make them, a multitude of minds have associated, united and combined their ideas and sentiments” for many generations (Durkheim, 1912, p. 29). Because Durkheim’s form of collective consciousness is more than the aggregation of individual actions, the exact mechanism for the formation of the collective is not clear in his work. However, Durkheim brings up cooperation between people; this is an essential component of forming collective

19 memories. Collective consciousness and collective memory are essentially interrelated but not identical. Collective consciousness refers to all of the conscious and unconscious thoughts shared by some particular group. The collective memory of a community is part of the collective consciousness, but memory refers to representations of the past, while the collective consciousness can include present and future expectations. The distinction between collective memory and collective consciousness is small, but the important difference, relevant to creating a unifying method of study, is that a collective consciousness includes societal norms, while the collective memory is influenced by those norms.

Maurice Halbwachs, a student of Durkheim, also discussed collective sociological phenomena. Halbwachs’ thesis was that a society can have a collective memory and that memory is dependent upon the "cadre" or the framework within which a group is situated in a society, or, in other words, the sociological context of the group. Halbwachs says that there is not only an individual memory, but also a group memory that exists outside of and lives beyond the individual. For Halbwachs, an individual's understanding of the past is strongly linked to this group consciousness. He says that people normally acquire their memories in society and that it is also in society that they recall, recognize, and localize their memories (Halbwachs & Coser,

[1925] 1992). Halbwachs is recognizing that every part of memory is inherently social; encoding memories is often a social process, retrieving and recalling memories is often social, and positioning memories in a world view or framework requires existing in the constraints of society.

Aby Warburg, a great 20th century and cultural historian, did not use the term collective memory, but nevertheless wrote about “social memory,” another term for the same phenomenon. Warburg studied the connection between artistic representation and the social

20 world. He accounted for two distinct but interwoven factors: first, the full spectrum of work, or the context of the artistic work in a given and, second, the independence and uniqueness of an individual . Warburg worked to uncover the balance between an individual work of art and the larger culture surrounding it. Warburg’s methods for studying art are hugely applicable to how one studies memory. There is the individual memory, or the individual work of art, but there is also the context of the art/memory, the styles of the time, and influence from other contemporaries and predecessors (Confino, 1997).

We can think about collective memory as a body of knowledge, an attribute, and a process (Roediger & Abel, 2015). Communities often share common knowledge of events or facts. For example, in an experiment testing Americans’ recall of American presidents’ names and ordinal positions, there was highly consistent recall by college students over a 30-year time span and between adults recruited to the study with an online platform (Roediger & DeSoto,

2014). That result demonstrates stability in how presidents’ names and ordinal position in the succession of presidents are remembered in the American collective memory. Collective memory can also refer to an attribute, or an image of a group of people. Collective memory is shaped by

“knowledge structures that serve to narrate the story of a people” (Roediger & Abel, 2015, p.

359). For example, in an experiment investigating possible templates of younger and older American adults for the Civil War, World War II, and the Iraq War, a large majority of participants named the attack on Pearl Harbor, the D-Day invasion, and the dropping of atomic bombs on Hiroshima and Nagasaki as important events in World War II. These events represent a beginning, a middle, and an end of a narrative of US involvement in World War II. That result demonstrates the way collective memories often become characterized within a narrative structure. Another result of interest in the experiment was that although both older and younger

21 Americans remembered the same events, they rated the events differently. For example, older adults rated the dropping of atomic bombs on Japan positively (8.0 average on a 10-point scale), and younger Americans rated the event negatively (3.4 average) (Zaromb et al., 2014). That result demonstrates generational difference in the collective memory. Finally, collective memory can refer to a process in which the past is continually reshaped and fought over. For example,

Turkey and Armenia are still fighting over how the disputed genocide of Armenians in 1915 should be remembered (Üngör, 2014). The ability of collective memories to change and be reshaped present a lot of opportunities for changing negative collective memories, such as and incorrect ideas about health, just to name a few. These possibilities will be discussed in more detail in Part IV.

The Two Cultures of Collective Memory

In his article Collective Memory: The Two Cultures, Jeffrey Olick discusses the two competing conceptions of collective memory. His review of the problems plaguing collective memory studies are central to this thesis and to my goal of improving the methods used to study collective memory and collective phenomena more generally. Through Olick’s discussion, we see the disconnect between the two cultures of collective memory and the need for more interdisciplinary approaches.

The individualist culture and the collectivist culture are the two competing conceptions of collective memory; in other words, the main conflict that appears when discussing collective memory is the apparent opposition between the individual, inward qualities of memory and the collective, social qualities of memory. The first approach to collective memory that I will discuss is the more socially-driven method. This approach is based loosely on Halbwachs’ social

22 frameworks approach that “groups provide the definitions…by which particular events are subjectively defined as consequential” and “these definitions trigger different cognitive and neurological processes of storage” (Olick, 1999, p. 341). This approach sees the collective, represented by or commemorations, as having an identity of its own apart from the aggregation of individual memories and as being more than the sum of its parts (Halbwachs &

Coser, [1925] 1992; Confino, 1997; Olick, 1999; Durkheim, 1912). This is supported both by (a.) aggregation effects that cannot be predicted from individual responses and (b.) by durable societal structures and who seem to control what a society or group can and should remember (Olick, 1999). Examples of these societal structures are things like norms that govern behavior, educational systems, and religious beliefs. Other for the collectivist approach focus on the reciprocal and interconnected nature of communities and individuals.

Robert Bellah has argued that genuine communities are communities of memory, and these communities of memory form constitutional that are told and retold so that the individual and collective identity of group members are inexplicably linked. Perhaps most importantly for our discussion, the collective memory approach emphasizes factors outside of an individual’s brain. For example, language itself can be seen as a memory system. Language is used primarily for communication between people; it is not isolated in the minds of individuals

(Bakhtin, 1986).

The collectivist approach has significant drawbacks. Our previous discussion of Emile

Durkheim’s work on collective consciousness revealed how difficult it is to elucidate a mechanism for the formation, maintenance, and alteration of a community’s collective memory using the purely social approach. It is difficult to measure a collective memory empirically or

23 objectively in this approach because the collective and representations of the collective cannot be measured in individuals.

The second approach to studying collective memory is based on the “aggregated individual memories of members of a group” (Olick, 1999, p. 338). This approach is based on the that only individuals remember; memory is an individual phenomenon that takes place in the brains of singular people. Olick argues that a better term for the individual approach to memory studies therefore may be “collected” memory rather than collective memory. This approach “locates shared memories in individual minds and sees collective outcomes as aggregated individual processes,” leaving the collected memory approach “open to the investigation of psychological or even neurological factors in social memory outcomes” (Olick,

1999, p. 339-340). The collected memory approach has several advantages; namely, this approach does not necessarily start with an assumption that a group has a collective memory, it is not susceptible to the politically- or socially-driven exclusions of certain memories from a group collective, and it resists forcing a certain identifying category, such as a national identity, on the individual. The large disadvantage of the collected memory approach is that it tempts researchers to “treat the human mind as something of a black box” (Olick, 1999, p. 340), and the methods used to study the memories of individuals often leave out the impacts of natural settings on remembering (Neisser, 1982). The collected memory approach emphasizes the individual, the psychological, and the neurological but fails to incorporate social contexts and social influences on memory.

Psychologists employing the collected memory approach generally use either top-down or bottom-up methods to study how collective memories are formed and retained. In the top- down approach, researchers start with a collective memory then probe for cognitive processes

24 that could explain how the collective memory was formed or maintained. In the bottom-up approach, researchers start with a cognitive process then show how it plays a role in forming or maintaining a collective memory (Hirst et al., 2018).

Olick asserts, and I wholeheartedly agree, that we can use collective memory as a term for the wide variety of processes and outcomes, neurological, cognitive, personal, aggregated, and collective, and that “we need an enterprise not that allows neurological, cognitive, attitudinal, and cultural work to go on side by side, but that brings these enterprises into dialogue with one another” (Olick, 1999, p. 346). For we cannot speak of the collective without individual memories, and we cannot speak of individual memory without the massive impacts of community and context. A boundless number of social and neural networks are constantly interacting with one another, so we cannot study memory completely without investigating both the individual, the context, and the collective.

Social-Interactionist Approach

An emerging discourse on collective memory is using social-interactionist approaches, which I argue is the best approach to take when studying collective memory. Social-interactionist approaches are structurally closest to bottom-up “collected” memory approaches, but there are important differences between the two. The main difference is that social-interactionist approaches include the attenuation and facilitation of cognitive phenomena in social settings and how the phenomena propagate across large social networks; collected memory approaches only study the aggregate effect of individual memories without accounting for conversational influences.

25 Social-interactionist approaches to collective memory can be defined in three stages. In the first stage, relevant cognitive phenomena are identified, such as the effects of selective retrieval on memory (Vlasceanu et al., 2018b; Roediger & Abel, 2015; Weldon, 2000;

Murayama et al., 2014; Marsh, 2007; Geana et al., 2019). In the second stage, the attenuation and facilitation of individual in social settings is investigated. An example of the process in this stage is the measurement of the degree of reinforcement or forgetting of items after selective, conversational remembering in dyadic conversations (Vlasceanu et al., 2018a; Vlasceanu et al.,

2018b). The third stage involves conducting social network research to see how social influences on memory propagate across a community (Vlasceanu et al., 2018b; Epstein, 2006).

Experimenters who follow this approach have found significant effects for conversation on collective remembering. Again, this approach starts with individual cognitive phenomena, most notably, retrieval-induced forgetting (RIF), which was discussed in Part I. The underlying factor to RIF is the fact that memory retrieval is selective (Marsh, 2007; Murayama et al., 2014).

At the dyadic conversational level, the speaker and the listener remember and retrieve concurrently (Coman et al., 2016). In the speaker, the individual cognitive phenomena of RIF and the retrieval reinforcement effect are still at play. In the listener, the two effects are now called the socially shared reinforcement effect (SSR) and socially shared retrieval-induced forgetting (SSRIF) (Coman & Hirst, 2012; Coman & Hirst, 2015; Eitam & Higgins, 2010).

To test how the formation of collective memories is dependent on individual-level phenomena, namely, selective reinforcement and forgetting, Alin Coman et al. conducted an experiment in laboratory-created communities (Coman et al., 2015). First, participants learned four items of information for each four Corps volunteers in the study phase (16 items total). In the pre-conversational recall phase, participants were cued with the name of the

26 volunteer and tested on their individual recall of the previously studied information. In the conversational recall phase, participants in 10-membered communities were paired up for a series of dyadic conversations during which the conversation partners jointly remembered the study materials. After the conversational recall phase, participants were again asked to individually remember the studied information in the post-conversational recall phase. Data was collected in each phase and analyzed. The dependent variables calculated include similarity scores, mnemonic convergence scores, mnemonic alignment scores, mnemonic difference scores, and item centrality. Mnemonic similarity is the similarity between the memories of any two participants, computed both pre- and post-conversation. Mnemonic convergence is the average of mnemonic similarity scores across a network, computed both pre- and post-conversation. Mnemonic alignment refers to changes in mnemonic similarity scores between any two participants from pre- to post-conversation. Mnemonic difference is the difference between a participant’s pre- and post-conversation recall, measured for each item separately. Item centrality is the centrality of an item in the collective memory of a community, computed both pre- and post-conversation. To compute these variables, the researchers also had to assign reinforcement/suppression (R/S) scores for each of the 16 studied items for each participant. If an item was mentioned during a conversation, it was labeled Rp+ (retrieval practice plus). If an item was not mentioned during a conversation but was related to a mentioned item, it was labeled Rp- (retrieval practice minus). Nrp (no retrieval practice) items that were unmentioned and unrelated received a score of zero on the R/S scale. If items were mentioned in all three conversations, that item for that participant would have an (+3) R/S score.

If an item was Rp- in two conversations but Rp+ in one conversation, that item for that participant would have a (-1) R/S score. This method of computing R/S scores is called mixed

27 R/S scores because the status of an item can change in different conversations. To calculate pure

R/S scores, you include only items that can be definitely characterized as suppressed, reinforced, or baseline. The items with positive R/S scores, both in the mixed and pure calculations, were reinforced, measured by a higher mnemonic difference score than the baseline items. Items with negative R/S scores were suppressed, shown by a significantly lower mnemonic difference score compared to the baseline items. The researchers also computed item centrality for each item and found that centrality was correlated with positive R/S scores. These results demonstrate that collective memory is shaped by the processes triggered during remembering and that “items that become central to the collective memory of a community are those that are mentioned frequently and are reinforced in conversations among members of the community” (Coman et al., 2016, p.

8175).

Group membership also has influences on the degree to which listeners will concurrently retrieve with speakers and thus the degree to which they show SSR and SSRIF (Coman & Hirst,

2015). Epistemic motivation, or motivation to form a valid representation of the world, has been shown to influence the degree to which listeners concurrently retrieve with the speaker (Cuc et al., 2007). However, relational motives, or motivations that “induce people to affiliate and feel connected to others” (Echterhoff et al., 2009, p. 500), can also encourage listeners to concurrently retrieve with the speaker, particularly if the speaker belongs to the same as the listener (Coman & Hirst, 2015). People have a higher degree of relational motivation for those in their in-group than to those in their out-group (Echterhoff et al., 2009).

Coman and Hirst tested the effect of group membership on concurrent retrieval experimentally.

In the first experiment, Princeton students listening to a speaker on a video demonstrated SSRIF when the speaker was identified as another Princeton student but did not demonstrate SSRIF

28 when the speaker was identified as a Yale student. In the second experiment, the Princeton student participants were given a survey that activated a common student identity before they listened to the speakers. This activation of a common student identity between Yale and

Princeton students triggered concurrent retrieval and SSRIF when the participants listened to both Princeton and Yale students. Coman and Hirst’s experiment testing the effects of group membership on degree of concurrent retrieval and SSRIF demonstrated that “collective forgetting arising from selective remembering is more likely to emerge when speaker and listener share group membership” (Coman & Hirst, 2015, p. 721). In the first experiment, the

Princeton students were focused on their identity as Princeton students, separate from Yale students. In the second experiment, Princeton students were focused on their identity as college students. The differing identities and their effects on remembering clearly show that group membership affects how individual memories are modified in the social sphere. Eitam and

Higgins propose that the common group membership effect might not be due to shared social identity but instead due to increased relevance of what the speaker is saying to the listener (Eitam

& Higgins, 2010). However, whether the increased concurrent retrieval and SSRIF are due to relational motives or relevance, the result is “a tight connection between group membership and subsequent SSRIF” (Coman & Hirst, 2015, p. 721).

Conversational influences play a large role in shaping the individual memories of the conversation partners, but dyadic-level conversational influences on individual memories only facilitate the formation of collective memories if the propagates across the community. Geana et al. experimentally studied how the structure of the social network, namely the degree of clustering and reachability in the network, impact the formation of collective memories in a community. They used nine 16-member networks in which each participant first

29 studied a story of what happened to a fictional character over a 6-day period. Each day had an event that corresponded to it. The participants first independently recalled the story in the pre- conversational recall phase, then each participant jointly recalled the story in a sequence of 2-4 dyadic conversations in the conversational recall phase. The participants then independently recalled the story again in the post-conversational recall phase. Four different network structure types were used to test the influence of network structure on the formation of collective memories: high-clustering/low reachability network, high-clustering/low reachability network, low-clustering/low reachability network, and low-clustering/high reachability network.

Clustering refers to the degree of clustering of smaller groups within a network, and reachability refers to the ability of information to reach other members in the network. A highly clustered 16- member network might have a group of 5 members, two groups of 4 members, and a group of 3 members with each smaller group connected to the others only through one node. Real-world communities generally have a high clustering coefficient and high reachability. The researchers found that highly clustered networks showed a larger increase in mnemonic convergence from pre- to post-conversation than less clustered networks and that clustered networks show more alignment with the community collective memory with each conversation than low-clustering networks. Reachability did not show any significant results.

Geana et al. then examined the role of connections between clusters, called bridge ties, on synchronization of memories in clustered networks. In one condition, the Complete Bridge condition, each cluster is connected, and in the other condition, the Absent Bridge condition, there is a link missing between two clusters. In the real work, an example of a bridge tie is a friend talking to people in one friend group, then telling people in a different friend group what was discussed in the other group. The Complete Bridge network showed a higher cross-cluster

30 mnemonic similarity score than the Absent Bridge network, indicating a more convergent collective memory. Finally, Geana et al. tested whether an individual’s centrality in the network impacts the collective memory. They tested both topological centrality, a participant’s location in the network, and temporal primacy, the timing/earliness of the participant’s conversations. They found that both topological centrality and temporal primacy have significant effects on a community’s collective memory; those individuals who speak earlier and are more central in the network are “more influential in shaping the collective memory of the community than peripheral individuals” (Geanu et al., 2019, p. 5). This research is important for several .

First, it demonstrates that network clustering plays an important role in the formation of collective memories. Second, the fact that the experimental network most similar to real-world social networks (high-clustering/high reachability) showed the highest level of mnemonic convergence suggests that real-world communities are well equipped to form collective memories. Third, these results can provide clues on how best to form social networks in groups like classrooms and companies to achieve either convergent or divergent collective memories.

While the social-interactionist approach I have described includes the effects of social sharing of memories, it does not include the context effect of overarching societal institutions.

From our discussion of individual memory, we know that context and individuals’ preexisting state of knowledge have huge effects on what and how we remember. We anchor new information to related, previously-stored information and, therefore, we conceptualize new information in the context of our previous life experience. Every society has norms that govern behavior, oftentimes without the conscious knowledge of the individual actor. In Durkheim’s view, the collective is over and a part of every member of society. Durkheim says that “there are two in [a person]: an individual being…and a social being which represents the highest

31 reality in the intellectual and moral order” (Durkheim, [1912]1961, p. 29). There is no individual apart from the collective, “man is double” (Durkheim, [1912]1961, p. 29). If the collective, or the norms governing how members of a society act, exists within the individual, the individual is controlled by the collective even if they are not aware of this control. Norms, mores, or collective consciousness define all of society’s thoughts and actions. It is very difficult to escape something that is inside of you.

Because these societal influences and institutional constraints are important forms of context, they need to be represented in our investigation of collective memory. I propose integration of these influences into the social-interactionist approach. The exact way to perform this integration is not altogether straightforward, but it is crucial to include if we want to analyze the full picture of formation of collective memories in communities. One could potentially include the influence of societal context by quantifying the degree of individual’s integration into certain institutions such as educational or religious institutions or by using variables such as the specific textbook narrative someone was taught in school about a certain event to measure the degree of divergence in memory between people who learned different in textbooks.

Nonetheless, more focus should be given to the influence of societal constraints on collective memory.

32 Part III: Case Study

Civil War Memories: Generational Shifts and False Memories

Memory of the Civil War in the South presents an interesting case of collective memory.

The story of Southern memory of the Civil War demonstrates features of generational differences, false memories, retrieval-induced forgetting, influences from societal institutions, and divergent collective memories.

In Texas and across the South, a collective memory emerged after the Confederate defeat that the Confederacy fought a noble fight to preserve states’ . We know from primary source evidence that was in fact central to Southern secession, but that fact was forgotten from the collective memory due to various factors, including socially shared retrieval-induced forgetting and contextual reinforcment. The more that it was repeated that the South fought a noble fight for states’ rights, the more the causative nature of slavery was forgotten from the collective memory.

33 The maps above, taken from Walter Buegner’s book Secession and the Union in Texas, display ethnic settlements across the counties of Texas in 1850 and the percentage vote for secession by county in 1861. If we compare the two maps, we can see that counties with a higher black population, which, in that time, meant a higher slave population, were more likely to vote to secede in 1861. In the Texas valley where there was little to no slave population, the counties voted against secession. This is evidence for slavery as the principal cause of the Civil War.

Other evidence includes Texas’ declaration of causes at the 1861 Texas for succession, which states: “Texas…was received as a commonwealth holding, maintaining and protecting the known as negro slavery—the servitude of the African to the white race within her limits—a relation that had existed from the first settlement of her wilderness by the white race, and which her people intended should exist in all future time” (Texas et al., 1912, p.

62). Clearly, slavery was central to the decision to secede.

By about 1870, states’ rights appeared as a justification for the Civil War, when that assertion in 1861 would have been ludicrous. This idea was first formed into collective memory through conversational effects on individual memories that propagated through the society.

Then, the rewriting of the Civil War was solidified in Southern collective memory through monuments, commemorations, and groups that celebrated Confederate heritage. Furthermore, in the time since the Civil War, the narrative of Southern nobility and honor was continually reinforced by textbooks used in Texas schools. Textbooks form the curricular foundation for most American history classrooms. Given their outsized importance, the narratives presented in textbooks impact both teacher choices and student understanding of the wars our nation has fought (Pearcy, 2014). If students learn a Southern-sensitive version of the Civil War in textbooks, that memory will form the basis of future associations with the Civil War formed in

34 neural networks. The manner in which such wars are presented to our students, then, is a vital issue for educators and all citizens.

To demonstrate some of the factors contributing to Southern collective memory of the

Civil War, I provide a personal story. I am an eighth-generation Texan, and my is very proud of that fact. Growing up, we celebrated Texas Independence Day, and I often heard stories about my ancestors’ involvement in Texas history. I am proud to be a Texan, but my conception of our family’s place in history is different than my father’s and much different than my grandfather’s. This difference is due to the fact that each generation learned about our history in a different historical context. One source of shame for me that separates me from my ancestors’ collective memory is my family’s involvement in the Confederate army. When my grandfather was still alive (when I was under 10 years old), he would take me to an event every year called the Southern Heritage Ball. It was a celebration of Robert E. Lee’s birthday combined with a debutante presentation in which all of the debutantes were descendants of Confederate veterans.

People dressed up in fancy ball gowns, sometimes in the of the 1800s, danced, and ate. I had a wonderful time, and those are some of my fondest memories with my grandfather. I had no conception that the preservation of slavery was the root cause of the Civil War (or, for that matter, intertwined with the causes of the Texas Revolution). What is the for my grandfather’s taking me to a ball every year celebrating a man who fought a war for slavery? Is the explanation that my grandfather was a bad person? Some would argue that, but if we look at how collective memory works, it seems that there is more nuance there.

In the time in which my grandfather grew up, and for most of his life, the Southern collective memory of the Civil War had long forgotten the central feature of the Civil War: slavery. The collective memory of the Civil War included a set of facts, such as that states’ rights

35 were the cause of succession, and a constitutive narrative, an image of a people. The false

Southern narrative of the Civil War defined what it was to be a white southerner; it became part of Southern identity and heritage. My grandfather subscribed to a more Anglo-centric view of

Texas because of the societal context he grew up in, the incorrect Southern narrative’s mediation of his interpretation of the world, and reinforcement of that narrative through socially shared reinforcement effects. It was actually not until a few years ago that history textbooks in Texas changed to citing slavery as the principle cause of the Civil War. On the other hand, I have a much different conception of the Civil War than my grandfather did. The Southern narrative was part of my identity, but contextual factors have changed. While I still identify as a Texan and a

Southerner, proactive interference has changed my memory of the Civil War. As a child, I was taught the things that my grandfather believed and felt pride when I went to the Southern

Heritage Ball, but new knowledge has interfered with and replaced the incorrect and offensive attributes of my early memory of the Civil War, changing both my bank of knowledge and my constitutive narrative. My family’s story mirrors many other Southern ’ stories of generational differences in views about the Civil War. The changes in my individual memory and conception of the Civil War reflect a change that has happened and is in the process of happening in many other people who identify as Texans, or Southerners, or descendants of

Confederate soldiers. The changes in my individual memory would not be possible if the collective memory and collective consciousness regarding the study of history had not been reshaped, and the collective cannot be reshaped until individuals start talking to each other and create a new narrative that propagates across a community. This reciprocal process between the individual memory and the collective memory, all under the umbrella of the collective consciousness, have led to the shifts over time in Southerners’ collective memory of the Civil

36 War, with each generation generally moving towards a more inclusive and accurate understanding of the war.

Despite this and reshaping, the false Southern collective memory still exists in some groups, which has been demonstrated by debates over removal of Confederate monuments.

Those who still hold the Southern narrative as their constitutive narrative see these monuments as monuments to their heritage and to the valor of their ancestors, while others see the monuments as offensive remnants of an incorrect version of history. Tensions between divergent collective memories like these arise because collective memories are so much more than shared knowledge of facts and events; they are central to personal and group identities and provide a lens for how people view the world.

37 Part IV: Implications of Collective Memory Studies

Beyond modifying the methods for studying collective memory and understanding the phenomenon for understanding’s sake, the study of collective memory could have important implications in the real world. Collective memories are important in part because they affect peoples’ attitudes, decisions, and how they collectively solve problems (Coman et al., 2016).

While the malleability of individual and collective memory by conversational influences can be seen as a negative, some argue that these properties are adaptively valuable in promoting socialization (Hirst et al., 2014; Schacter et al., 2011). Convergent collective memories promote social binding of communities (Bluck et al., 2005) and could help solve social problems such as rapid information sharing in public health crises like the COVID-19 pandemic, reducing stereotypes, and promoting social , among many other possible applications.

Collective memories have been shown to affect people’s attitudes. First of all, individuals usually approach a topic with a specific , and “attitudinal selectivity people’s memory in favor of information they agree with” (Coman & Hirst, 2011, p. 322). However, changes in memory lead to changes in attitude, and vehicles such as political speeches can have huge influences in shaping the memories and attitudes of individuals, especially if the listener spends significant time after hearing the speech engaging with like-minded others (Coman &

Hirst, 2011). Furthermore, collective memories influence people’s decisions (Kameda et al.,

1997) and how they collectively solve problems. Many have argued that the so-called

“imperfections” of memory are actually adaptive when viewed through the lens of promoting a collective memory. Humans have arguably developed their advanced cognition and syntax in order to adapt to complex social situations, and Hirst et al. argue that “the contribution of practice effects, social contagion, and induced forgetting in promoting the formation of collective

38 memory suggests that we might add memory to this list of social ” (Hirst et al., 2014, p. 15). The mechanisms of human memory display a remarkable flexibility compared to something like computer memory.

Schacter et al. argues that “several types of memory distortions…reflect adaptive cognitive processes that contribute to the efficient functioning of memory, but produce distortions as a consequence of doing so” (Schacter et al., 2011, p. 467). They study three types of memory distortions: inflation, gist-based and associative memory errors, and post-event misinformation. happens when imagining a novel event leads people to increased confidence that event actually occurred in their personal past. Imagination inflation is a form of false memory that was discussed in Part I. Neuroimaging studies have shown that imagining possible future events and remembering past events share the same core network, suggesting that imagination and memory can be easily confused. Schacter et al. argue that this imagination distortion is adaptive because episodic memory’s primary function is to prepare for the future by using stored information to construct a simulation of a future event.

Gist-based errors and associative errors are distortions like extra-list intrusions (see Part I).

Associative memory serves an adaptive value by assisting memory performance in providing a structure and organization for new stimuli to anchor; however, it also has a cost: false memories and vague memories. Post-event misinformation refers to proactive interference that inserted incorrect, conflicting information into a memory engram. These distortions serve an adaptive function: “they reflect a dynamic memory system that flexibly incorporates relevant new information in order to update memory” (Schacter et al., 2011, p. 470). Harnessing these adaptive features of memory along with other aspects of information propagation in social

39 networks could lead to development of highly effective strategies for improving communities, health, and justice.

Furthermore, the social-interactionist approach I describe in Part II has powerful potential for application in public policy. Public policy outcomes can be more impactful with the social- interactionist approach because of its large-scale nature and predictive power. For example, using a social-interactionist approach, Damon Centola, like Geana et al. (see Part II), found experimental evidence that clustered networks are more efficient in spreading information and creating a converging collective memory in communities than random networks. Centola tested this network structure with an experiment aimed at diffusing health behaviors across a community. He found that “not only is individual adoption [of health behaviors] improved by reinforcing signals that come from clustered social ties, but this individual level effect also translates into a system-level phenomenon where-by large-scale diffusion can reach more people and spread more quickly in clustered networks” (Centola, 2010, p. 1197). These results can inform how public health interventions are performed. The results suggest that targeting clustered residential networks is the most efficient way to diffuse adoption of positive health behaviors through a community. In the current context of COVID-19, there has been much confusion in the public about what the social distancing rules are and what the features of the virus are. Government officials may do better and achieve wider adoption of the recommended guidelines if they use a clustered network approach to disseminating information.

Other applications of knowledge from collective memory research include creating effective strategies for promoting and diminishing stereotypes. There is a in communication chains for -consistent information over stereotype-inconsistent information, and this bias is driven by conversational processes rather than general memory bias.

40 When people identify as having a shared identity, they have actual sharedness of knowledge and perceived sharedness of knowledge, meaning that people believe that other members of the community share the same knowledge. This perceived sharedness may be underlying the bias toward stereotype-consistent information, and actual sharedness definitely plays a role in the continued maintenance of stereotypes (Lyons & Kashima, 2003). The sharedness Lyons and

Kashima refer to is the collective memory of a group. If the sharing of stereotypes in collective memory is what is allowing stereotypes to persist, then inserting a new narrative, or stereotype- inconsistent information, into the collective memory could eventually eliminate stereotype information that promotes racist ideas, sexist ideas, and other ideas that negatively affect communities.

Another interesting point to study would be the effect of social media on information propagation. In the social media space, individuals are constantly in dialogue with other people, perhaps even more so than face-to-face conversations. I predict that this increased level of interaction with other members in one’s community will increase the speed of convergence of collective memories but also produce an increasing number of divergent collective memories with greater strength based on the type of content and accounts one interacts with most frequently.

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48 Abigail V. Aldis was born in Houston, Texas on August 19, 1998. She attended Westside High School, then attended the University of Texas at Austin. She graduated in May 2020 with a Bachelor of in Plan II and a Bachelor of Science and Arts in Neuroscience with a minor in history. In college, she was an active member of Kappa Delta sorority, worked as a Ambassador with UT Counseling and Mental Health Services, travelled with UT Global Medical Training on a medical service trip to Peru, and volunteered at a local Austin homeless feeding program. She joined the Teach for America 2020 Corps and plans to teach high school science at a Title I school in Charlotte, North Carolina for two or three years before attending medical school.

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