1,001 Nights of Dream Recall

1,001 Nights of Dream Recall by Kelly BulkeleyBetween January 8, 2015 and October 4, 2017, I remembered and recorded a dream every night for 1,001 consecutive nights.  Now I’m studying the dreams and trying to find insights that can help in exploring the dream series of other people.  I don’t expect anyone to accept my personal dreams as conclusive evidence for any general theory of human dreaming.  Instead, I offer them as way of being transparent about the experiential grounding of my research pursuits.  This is one of the ways I get ideas for new projects.

All of the dreams are available online for further study in the SDDb, in the “Sample Data” section.

From a scientific perspective, the value of an introspective project such as this is to generate working hypotheses for future studies.  Trying to study another person’s long diary of dreams can be very challenging, especially at the outset when the researcher is facing a huge mass of texts with multiple dimensions of meaning.  I appreciate anything that can provide some initial orientation and help to steer the direction of the analysis.  By studying my own dreams, which I know from both a first- and third-person perspective, I can quickly and easily identify some patterns of meaning that seem worth further exploration.   Maybe they will apply to someone else’s dream series, maybe they won’t; either way, it helps the analytic process get going.

Remembering and Recording the Dreams

The method I use for keeping my dream journal is fairly typical.  I keep a pad of paper and a pen by my bedside, and when I wake up in the morning I immediately write down whatever dreams I can remember, before getting out of bed or turning on the light.  Then later in the morning I type the dream into a digital file, along with associations, memories, and thoughts about what the dream might mean.

During the three years of recording this series of 1,001 dreams, I did my best to wake up slowly each morning, so the images and feelings from the preceding dreams could coalesce in my memory.  I don’t believe I dreamed more during this time than I did in previous periods of my life; rather, I devoted more energy to remembering the wispier, more evanescent kinds of dreams that, in previous years, had not crossed the threshold into waking memory.  I made a more determined effort to protect the space around the transition from sleeping to waking, even during circumstances when that was difficult to do (e.g., on international plane flights, during family holidays).  Often it took a few moments of quietly lying in bed with my eyes closed before the vague feeling “I know I was just dreaming,” could eventually take form into a specific memory of what I was just dreaming about.  Often there were “aha!” moments when suddenly a whole long dream came back to me, which I surely would have forgotten if I had immediately leapt out of bed upon awakening.

I also put more conscious intention into the other end of the transition, from waking into sleeping, as I carefully set up my journal and pen each night before turning out the light.  I did not set specific dream incubation questions during this time, but simply tried to signal to myself that I was ready and willing to record whatever dreams might come during that night’s sleep.

These were not extreme or burdensome behaviors; they required consistency of purpose, but no heroic feats of will.  I never set any long-term goals or numerical targets.  Instead, I just focused on each new night and each new dream, figuring the time would come when I could survey the series from a broader perspective.

About a month ago I finally did the math, and realized that October 4th would mark 1,001 nights of dream recall in a row, an enchanting milestone.  This seemed like a large enough collection of dreams to pause, look back, and see what I could learn.

Patterns of Word Usage

The reports comprise a total of 93,050 words, with an average length per dream report of 93 words, and a median length of 73 words.  The shortest dream in the series has 9 words, and the longest has 728 words.  The average length of these dreams is not unusual, compared to other people whose dreams have been analyzed in this way.  Some people have much longer dreams than I do, and some people have much shorter dreams.  This series of 1,001 dreams, then, includes mostly dreams of middling length.

To highlight the patterns and themes in a series like this, I start by comparing it to what I call the “SDDb baselines,” two large collections of male (N=2,135) and female (N=3,110) dreams that have been systematically gathered and analyzed using a template of 8 classes and 40 categories of word usage.   I use the baselines a measuring stick for identifying possible continuities and discontinuities between the dreams and the individual’s waking life.

The results of this comparative analysis are presented in an accompanying spreadsheet, “1001 Nights Data.”  Some of the discussion below draws on an earlier analysis I wrote about an overlapping set of my dreams.

In relation to the SDDb baselines (an average of 100 words per report for the females and 105 for the males), my dreams are a little shorter than average (93 words per report).  The results for each of the 8 classes of word usage are summarized below.  Compared to the male and female baselines, my 1,001 dreams have:

  1. Perception: More references to vision and colors.
  2. Emotion: Many more references to wonder/confusion, and more to happiness.
  3. Characters: Fewer references to family characters (although the word “wife” is mentioned very frequently), more references to animals (especially cats), and slightly more references to females than males.
  4. Social Interactions: Slightly more references to sexuality.
  5. Movement: Fewer references to death.
  6. Cognition: More references to thought, fewer to speech.
  7. Culture: Fewer references to school, food/drink, religion, somewhat more to sports (especially baseball and basketball).
  8. Elements: More references to water, somewhat more to earth.

These findings provide the basis for a “blind analysis,” which means making predictions about continuities between these patterns of word usage in dreaming and the individual’s waking life activities, beliefs, and concerns.  If I pretend I knew nothing about the dreamer of these 1,001 dreams, and I only had these word usage frequencies to consider, I would infer this individual:

  1. Is visually oriented
  2. Often experiences wonder/confusion
  3. Is relatively happy
  4. Is married
  5. Cares about cats
  6. Has fairly equal relations with men and women
  7. Is sexually active
  8. Is not concerned about death
  9. Is not highly verbal
  10. Is not highly involved with schools
  11. Is not highly concerned about food/drink
  12. Is not highly concerned about religion
  13. Has lots of interactions with water and earth

1,001 Nights of Dream Recall by Kelly BulkeleyMost of these inferences—I’d say 11 of 13—are unmistakably accurate in identifying a continuity between a pattern of dream content and an aspect of my waking life concerns.  The two I would question are numbers 10 and 12.  Regarding the low frequency of dream references to school, I do in fact engage in a great deal of teaching and educational work, but it’s almost entirely online, and I rarely set foot inside a traditional school any more.  Also, I no longer have school-age children living at home.  So it seems my dreams are continuous with my physical behaviors relating to schools, but not with my computer-mediated educational activities.

Regarding the low frequency of religion references, I most certainly do have great interest in religion, going back to my masters and doctoral studies at the Divinity Schools of Harvard and University of Chicago.  So the inference seems very wrong at this level.  And yet, at another level it seems more accurate.  I was not raised in a religious household, I do not personally identify with any official religious tradition, and I rarely attend religious worship services.  Compared to other people I’ve studied with very high frequencies of references to religion in their dreams, I am a much less personally pious person.  Perhaps what this suggests is that the dreams are accurately reflecting the fact that religion may be an important intellectual category for me, but it is not a personal concern.  My spiritual pursuits are more likely to be expressed in dreams with references to other word categories like water, art, sexuality, animals, and flying.

Shorter versus Longer Dreams

Earlier this year I looked at different set of my dreams to get some idea about possible differences between shorter and longer dreams.  This question rose in relevance when I realized, as noted earlier, that my increased recall seemed to depend in part on the recollection of relatively shorter dreams that in the past I did not fully remember or write down.

There were two main findings of that earlier study.  First, most of the patterns in content appeared in dreams of all lengths, from the shortest (less than 50 words per report) to the longest (more than 150 words per report).  Here’s a summary of what I found:

“The results of this analysis suggest that shorter dreams are not dramatically different from longer dreams in terms of the relative proportions of their word usage.  The raw percentages of word usage do rise from shorter to longer dreams, of course, but the relative proportions generally do not.”

Second, the longer dreams did have proportionally more references to a few word categories, chiefly Fear, Speech, Walking/Running, and Transportation. Another quote:

“These are the word categories that seem to be over-represented in longer dreams.  They are significant contributors to what makes long dreams so long.”

Returning to the present collection of 1,001 dreams, I divided the series at the median point into two groups: the shorter dreams (72 words or less, 500 reports total) and the longer dreams (73 words or more, 501 reports total).  I used the same SDDb word searching template with each of the two groups as I used with the full series, and then I compared their frequencies of word usage.  The biggest variations between the shorter and longer dreams appeared in the following categories:

  • Touch
  • Fear
  • Anger
  • Physical aggression
  • Walking/Running
  • Speech
  • Transportation
  • Water

This list adds a few other categories that may be characteristic of longer dreams.  Each of these categories has a dynamic quality.  Touch is a physical interaction.  Fear and anger are strong and unpredictable emotions, usually prompted by something in the external environment.  Physical aggression combines the previous categories (touch, fear, anger) and possibly intensifies them.  Walking/Running and Transportation both involve physical movement from one place to another.  Speech implies a context of interpersonal communication, people talking with each other.  Water, the “universal solvent,” is ever-shifting in its states (gas, liquid, solid) and its movement through human life.

When these elements appear in my dreams they seem to have the effect of expanding the range of experience, stimulating more interactions, and lengthening the narrative.

Conclusion

I don’t know if any of this applies to anyone else’s dreams.  I do, though, believe that several of the insights gained here can provide working hypotheses for studying other series of dreams.  I will be keeping these ideas in mind as I explore new dream series:

  • The recall and recording methods of the dreamer influence the types of dreams included in the series.
  • Personal relationships are an area of especially strong continuity between waking and dreaming life.
  • The use of religion-related words in dreams may be discontinuous with spiritual interests in waking life.
  • Shorter dreams have mostly the same general proportions and patterns of content as found in longer dreams.
  • Longer dreams tend to include more dynamic elements.

 

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Notes:

The accompanying spreadsheet can be found here:

https://www.academia.edu/35024762/1001_Nights_Data.xlsx

More description of the SDDb baselines can be found in Big Dreams: The Science of Dreaming and the Origins of Religion (New York: Oxford University Press, 2016).

The earlier study of short versus long dreams can be found here:

Short vs. Long Dreams: Are There Any Differences in Content?

 

The Distinguishing Features of Big Dreams

The Distinguishing Features of Big Dreams by Kelly BulkeleyIf someone presented you with two sets of dreams, one of most recent dreams and one of highly memorable dreams, you could predict with a high degree of confidence which type of dream was in which set, based only on word usage frequencies.

The set with more references to flying, air, family, animals, fantastic beings, Christianity, and death is more likely to consist of highly memorable dreams.

This is a testable hypothesis that emerges out of a comparison of the SDDb baselines for most recent dreams (MRDs) and highly memorable dreams (MemDs), available here.  To be clear, it’s a prediction of probability, not certainty.  Some highly memorable dreams have none of these elements, while some most recent dreams have several of them.  But according to the SDDb baselines, it is the statistical tendency of highly memorable dreams to contain significantly more of these elements than we generally find in most recent dreams.

Whether or not this hypothesis has any practical application, it adds new evidence in support of the theoretical claim that dreams are meaningfully structured not just for the individual dreamer but also in relation to each other.  There really are different types of dreams, and their differences can be expressed in increasingly precise terms.

Other researchers such as Harry Hunt and Don Kuiken have proposed psychological models to account for different types of dreams (what Hunt calls “the multiplicity of dreams”).  I am not yet at the point with the SDDb baselines to feel comfortable engaging directly with their approaches, but that is definitely a long-term goal.

At this stage I want to look more closely at the higher-frequency MemD elements and try to understand what they might contribute to the dreams’ long-term impact on waking awareness.

Flying: Not all dream references to flying involve magical powers–some relate to the flight of birds, or flying on airplanes, or floating in water, or time “flying” by.  But many of the references are indeed about people flying magically, and I think it makes good sense that overall, MemDs have significantly more flying references than MRDs.  I would be surprised if it were otherwise, based on the recurrence of magical flying dreams through cross-cultural history.  Genuine flying dreams tend to be quite vivid and realistic, and it’s reasonable to assume that such unusually stimulating sensations would make a lasting impact on waking awareness.

Air: Some of the air references occur in flying dreams, but in most MemDs the air references appear in different contexts: the dreamer is struggling to breathe, or facing a tornado, or noticing the wind blowing.  I don’t know about dreams of wind, but certainly with dreams of tornados and potential suffocation the memorability of the experience is likely to be very high.  A tornado is the most powerfully destructive form of air in nature, and suffocation is a perennial threat to human life, perhaps especially in sleep for people who snore or have apnea.

Family: References to family members appear often in MRDs; they appear even more often in MemDs.   I think it’s fair to say that most people’s strongest emotional relationships (both positive and negative) are with family members.  Thus it makes sense that their appearance in a dream correlates with high memorability.  Looking in more detail at the word search results, references to parents (e.g., mother, father, mom, dad) tend to be the highest, suggesting that dreams in which the individual is cast as a child or in a child’s role are more likely to be memorable.

Animals: Based on any of several different theories (psychoanalytic, developmental, evolutionary), it could be expected that MemDs would have a higher proportion of animals than MRDs.  Psychoanalytically, animals symbolize powerful instinctual energies. Developmentally, animals appear more often in children’s than in adults’ dreams, and MemDs are often recalled from early in childhood. In evolutionary terms, animals in dreams may reflect ancestral threats that we are innately primed to notice and remember.

Fantastic Beings: This category by definition includes characters who are not “real,” so their appearance in dreams naturally arouses some degree of heightened awareness and emotional impact.  Many of them are perceived as extremely frightening and dangerous to the life of the dreamer.  I was surprised by the SDDb baseline results that the MemDs do not have more fear-related emotions than the MRDs, but perhaps what makes some MemDs different is the supernatural source of the fear. There is a connection to be made here with the notion of “minimally counterintuitive supernatural agents” as used in the cognitive science of religion–dreaming is a rich experiential source of people’s religious and spiritual beliefs about such beings.

Christianity: Many references to Christianity in both MRDs and MemDs are relatively trivial references to Christmas, or mild oaths, or a person’s name.  But more often in the MemDs there are direct references to interactions with Jesus, battles with demons, visiting heaven, and worshipping in church.  In a majority-Christian country like the U.S., where all the SDDb baseline participants reside, this seems like an expectable result.  Insofar as Christianity, like most religions, is concerned with deep questions of morality, suffering, and faith, any dream that refers to religious teachings is likely to register more memorably in the dreamer’s awareness.

Death: Whether considered in religious or secular terms, death surely counts as a major existential concern of human life.  Dreaming itself has long been mythologically associated with death, and cultural traditions all over the world have stories about dreams as a portal to the afterlife.  In MemDs the theme of death takes many forms: other characters dying or being killed right in front of the dreamer, dead relatives appearing as if alive (i.e., visitation dreams), and, more rarely, the dreamer him or herself dying.  When the prospect of mortality arises in a dream, it’s not surprising that the individual takes notice and remembers.

What do these seven higher-frequency MemD elements have in common?

For one thing, several of them involve “counter-factuals,” i.e., phenomena that are literally impossible in ordinary waking life.  Magically flying in the air, encountering fantastic beings, seeing people who are dead appear as if alive–these are strikingly anomalous experiences that stand out from ordinary life and make a big impression on memory.

Secondly, several of the MemD themes involve dire threats to the individual’s life and well-being.  Dreams of death, demons, monsters, wild animals, suffocation, and tornados naturally arouse a host of psychological and physiological responses that can literally seize the dreamer’s attention and hold it long after waking.

Thirdly, a few MemD themes relate closely to the prominent themes of children’s dreams generally, with more animals and higher family references.  As I noted earlier, the SDDb baseline for MemDs includes numerous childhood-era dreams reported by children and adults, so it is definitely skewed toward children’s dream content.  That means the differences between MRDs and MemDs could be explained as artifacts of the differences between adults and children.  I grant there will be a large degree of overlap between highly memorable dreams and children’s dreams–precisely because the most memorable dreams people often recall are dreams from childhood.

Not all children’s dreams are big dreams–but many big dreams are dreams that have been remembered from childhood.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

A Primal Difference (Part 3 of Creating a Baseline for Studying Patterns in Dream Content)

A Primal Difference (Part 3 of Creating a Baseline for Studying Patterns in Dream Content) by Kelly BulkeleyWhat makes unusually memorable dreams different from average, ordinary dreams?  Putting it in Jungian terms, how are big dreams different from little dreams?

 

The SDDb baselines for most recent dreams (MRDs) and memorable dreams (MemDs) give a very precise and empirically based answer to this question.

 

MRDs tend to use more words relating to perception, emotion, cognition, social interactions, and culture.

 

MemD tend to use more words relating to flying, air, family, animals, fantastic beings, Christianity, and death.

Overall, MRDs are more anchored in present waking circumstances, while MemDs seem to have less connection to current social reality.   MRDs reflect more of daily life, while MemDs express deeper existential themes.

These results derive from 828 female MRDs and 691 male MRDs, compared to 801 female MemDs and 504 male MemDs.  You can see the spreadsheet here.

With the help of Dominic Luscinci at Far West Research, I analyzed these four sets of dreams in terms of their similarities and differences, adjusting the levels of statistical significance to account for multiple tests in each word class to protect against type 1 errors.  Fisher’s Exact Test was used in cases where the criteria for chi-square testing were not present.

Before getting into the MRD vs. MemD comparison, I wanted to know what gender differences were most significant. I found that female MRDs and MemDs are more likely than male reports of both types to include references to emotions (especially fear), characters (especially family), speech, and friendly social interactions.  Female MRDs have more perception and cognition, while male MRDs have more physical aggression and sexuality.

There are fewer gender differences in the MemDs than the MRDs.

Then I looked at the MRDs and the MemDs to see what differences show up for both males and females.  I found that MRDs for both genders have more references to emotion, cognition, social interactions, and culture.  MemDs have more references to nature (especially air and flying), characters (family, animals, fantastic beings), Christianity, and death.  The female MemDs have more fire, falling, and physical aggression words.  The male MemDs have more chromatic and achromatic colors.

There are many more differences between MRDs and MemDs than between the males and females.  The comparison with the fewest differences was female MemDs vs. male MemDs; these two sets of dreams were the most like each other.

My first reaction to these findings was surprise that the MRDs had more words relating to perception and emotion, since I expected these indices of intensity and vividness would be more frequent in highly memorable dreams.

But I also felt good because these results basically replicate a 2011 study I did with Ernest Hartmann on big dreams.  In the conclusion of that article we wrote “people’s big dreams are distinguished by a tendency toward ‘primal’ qualities of form and content: more intense imagery, more imagery picturing nightmarish emotions, more nature references, more physical aggression, more family characters, more fantastic/imaginary beings, and more magical happenings, along with less high-order cognition and less connection to ordinary daily surroundings.” (p. 165)

These findings are very similar to the SDDb baseline results.  They give me confidence that these differences between MRDs and MemDs are real and not the result of random variations in the data.

The comparison with the 2011 study is not perfect, since a) that project did not adjust the dream reports for word length, including reports of less than 50 and more than 300 words, unlike the SDDb baselines, b) some aspects of the conclusion (e.g., intense imagery, nightmarish emotions) were derived from Hartmann’s Central Image scoring system and did not emerge from the word search analysis, and c) the participant pool had a big gender imbalance (147 female, 15 male).  However, the mostly female composition of the 2011 study actually points to an even closer alignment with the SDDb female results because the female MemDs (but not the male MemDs) have higher frequencies of fire, falling, and physical aggression, all of which seem consistent with the 2011 study’s conclusion.

In a future post I will look at the SDDb’s high-frequency MemD elements–flying, air, family, animals, fantastic beings, Christianity, death–to try and discern what each of them adds to the dream’s memorability and impact on the dreamer.

 

SDDb Baselines for Recent Dreams and Memorable Dreams (Part 2 of Creating a Baseline for Studying Patterns in Dream Content)

SDDb Baselines for Recent Dreams and Memorable Dreams (Part 2 of Creating a Baseline for Studying Patterns in Dream Content) by Kelly Bulkeley“Dreams are not mysterious, supernatural, or esoteric phenomena.  They are not messages from the gods nor are they prophecies of the future.”  That’s what Calvin Hall said in his 1966 book The Meaning of Dreams (New York: McGraw-Hill, revised edition, p. 120).  Hall’s secular beliefs may or may not be justified, but what’s certain is that his baseline of “norm dreams” was designed to explain normal, average, ordinary types of dreams.  He was not interested in unusual, extraordinary types of dreams involving “esoteric phenomena.”  As a result, the baseline he developed gives what I call a homogenized view of dreams, privileging the theoretical significance of common, recently remembered dreams and denying the scientific relevance of rare but extremely memorable types of dreams from earlier times of life.

This is why I’ve created not one SDDb baseline, but two–one for most recent dreams (MRDs), and one for highly memorable dreams (MemDs).  You can find a spreadsheet with the baseline word usage frequencies here.  As always, I offer the caveat that this is a work in progress and will surely grow and change in the future.  My focus for now is to clarify some of the basic features of different types of dreams.  I’d like to know how MRDs and MemDs are similar, because that could tell us something interesting about how the sleeping mind operates consistently across varying dream types.  I’d also like to know how MRDs and MemDs are different, because that could tell us something interesting about the complexity of the mind in sleep and the creative potentials of the nocturnal imagination.  Setting up two baselines will, I hope, help the cause of answering these questions and provide a more sophisticated resource for the comparative analysis of other collections of dreams.

MRD Baseline: This includes 828 female dream reports and 691 male dream reports, all from the USA, all between 50 and 300 words in length, drawn from three sources.  The Hall and Van de Castle norm dreams (491 male, 490 female) form one component of the baseline.  This enables future analyses to maintain a solid “backwards compatibility” with the traditional standard of measurement in the dream research field, even as we continue trying to expand and improve beyond it. The additional dreams come from two SDDb sources: The Demographic Survey 2010, which included a “most recent dream” question, and the SCU Sleep/Wake Study 2008, which asked each participant to keep a dream journal and provide their two most recent dreams.  The SCU participants were college students like the HVDC norm dreams participants.  Those in the Demographic Survey were considerably older; I don’t yet have a detailed analysis of the age data, but I’m pretty sure the majority of participants were 50+ years of age.

MemD Baseline: This includes 801 female reports and 504 male reports, all from the USA, all between 50 and 300 words in length, drawn from four SDDb sources.  One is a question asking participants in the Demographic Survey 2010 to describe the earliest dream from childhood they can still remember.  Second is a question asking those same participants to describe the worst nightmare they can recall from any time in their life.  Third is a survey of children ages 8-18 asking them to describe the most memorable dream they’ve ever had.  Fourth is a survey of adults asking them to describe the most memorable dream they’ve ever had.  Unlike the MRD baseline, this one includes reports from children and reports answering different types of questions.  I have grouped these sources into a single baseline because they all fit comfortably under the heading “highly memorable dreams.”  Two of the sources use exactly that phrase in their questions, and the other two asked questions implicitly seeking reports of dreams with unusual memorability.  The inclusion of children’s reports is justified, I believe, because so many highly memorable dreams come from childhood, and thus children themselves may be in an especially good position to recall these dreams and describe them in detail.

At the far right of the spreadsheet you can see the word usage frequencies for each of these constituent sources of the two baselines.  As I said in the previous post, two important principles for creating a useful baseline are transparency and flexibility.  The baselines I’ve created have their limits, but they offer a great deal of transparency–you can see exactly where the reports are coming from–and flexibility–you can change or revise the baselines to suit your own purposes.

In the next post of this series, I’ll talk about some of the initial patterns I see in comparing the MRD and MemD baselines.  I invite your thoughts and observations! And corrections where I’ve gotten something wrong…

 

 

Creating a Baseline for Studying Patterns in Dream Content (Part 1)

Creating a Baseline for Studying Patterns in Dream Content (Part 1) by Kelly BulkeleyCompared to what?

 

That’s a question I’ve learned from Tracey Kahan to ask whenever I study a set or series of dreams.  If I find, for example, that 13% of a given collection of dreams include words related to fire, I can only assess the significance of that number in comparison to some other collection of dreams.  Maybe 13% is unusually high, maybe it’s unusually low; we can’t say for sure unless we have some kind of standard or baseline against which to compare it.

 

For the past half century, the Hall and Van de Castle (HVDC) Norm Dreams have been used as a general baseline to compare the content analysis findings of other sets or series of dreams.   No disrespect to Hall or Van de Castle, but I’ve always thought it would be good for the field of dream studies to develop a baseline that includes input from more than just 200 college students from 1950’s Ohio. We have indeed learned a great deal from that set of dreams, and now it’s time to widen our perspective.  One of my goals with the SDDb is to expand the HVDC approach by creating a bigger and better baseline for studying patterns in dream content.

Any dream research baseline, short of a total collection of all human dreams ever experienced, will inevitably be partial and limited, a tiny fraction of the totality of human dreaming.  This fact imposes an obligation of humility on those who pursue this kind of research.  A baseline is a pragmatic tool we create and use to help answer our questions, not a perfect representation of objective reality.

That said, it is not only possible but extremely important to make reasonable distinctions between better and worse baselines.

The bigger and more broadly based, the better.  The larger the database, the more likely the patterns in content are genuine and not just statistical noise (though we can never be absolutely sure).

Always, always, quality of data is essential–garbage in, garbage out, no matter how big your N.

The baseline’s sources should be very transparent, so researchers can make informed decisions about how much weight to give the results comparing their data with the baseline.

The HVDC Norm Dreams are divided by gender, and I think this is a good practice to continue for a couple of reasons.  First, there do seem to be significant differences between male and female dreaming, so creating a baseline for each gender offers a more precise tool for comparative research.  Second, many studies have a drastic imbalance in the gender of their participants, specifically a much higher proportion of female than male dream reports.  Hence the practical importance of offering a baseline for each gender, to facilitate the analysis of these kinds of imbalanced sets. (Why it’s easier to gather female than male dreams is a separate topic of discussion.)

Baseline frequencies for dream content will be sensitive to the word counts of the reports.  A collection of extremely long dreams will likely have higher frequencies of ALL categories of content, while a collection of extremely short dreams will likely have lower frequencies across the board.  The HVDC set draws the line at 50 words minimum and 300 words maximum.  I’m willing for now to go along with that policy, though eventually I want to return to consider what we may be losing by excluding shorter and longer dream reports.

What types of dreams should be included in a general baseline for dream research?  That’s a trickier question.  Should it blend together many different types of dreams, or should it concentrate on a single generic type of dream?

Many researchers have opted for the latter approach. The HVDC Norm Dreams include five dream reports from each participant, presumably recent dreams from the previous few nights, although several of the dreams are recurrent and/or come from an earlier time of life.  It’s not a “pure” set, but it purports to be a reasonable selection of the average dreams of this group of people.

Sleep laboratory researchers like David Foulkes have argued that dreams gathered in a home setting are too unreliable and only dream reports gathered in a controlled laboratory setting with accompanying sleep stage data should be considered when assessing basic patterns in dream content.  However, Bill Domhoff has made the case that dream reports gathered outside the lab setting can also be a valid source of insight, especially questionnaires asking people to describe their “most recent dreams.”

The difficulty in defining what counts as the most generic type of dream makes this approach problematic.  Another drawback is the under-reporting of the incidence of rare but intense and highly memorable types of dreams–nightmares, lucid dreams, visitation dreams, recurrent childhood dreams, etc.  These exceptional types of dreams may not occur as frequently as ordinary dreams, and thus they do not appear as often when people are asked to describe their most recent dreams.  But these unusual dream types are widely experienced and reflect important features of the dreaming mind that we need to account for in any general theory of dream psychology.  We lose sight of those features when we focus only on allegedly “average” dreams.

The advent of database technology makes it easier than ever to try the former approach: Creating a baseline that accepts rather than denies the “multiplicity of dreams” (in Harry Hunt’s terms), a baseline that blends together many different types of dreams and seeks a dynamic balance representing the varied phenomenology of dreaming across the widest possible range of its occurrence.

In Part 2 I’ll describe how I’m trying to develop this kind of blended baseline using data in the SDDb.