(Fiftieth Anniversary Issue) pages 121-134.

For the first two and a half years, the Lab merely listed the stories in order, from the most popular in first place down to those near the bottom. The Lab for October 1940 introduced a more precise system. Votes for each story were tallied. Each first-place vote gave the story one point; second place gave two points; third place three points, and so on. The total number of points for each story was added, then divided by the number of people voting on that story. For the first fifteen years, the Lab was just used to express reader opinions and guide the editor in deciding which authors to emphasize, but from 1953 onward, the authors that came out on top were given a cash bonus.

The impulse to analyze science fiction scientifically has gripped many readers over the years. For example, John A. Leiter, an Oregon attorney, quantitatively expressed his personal opinions about authors and their fiction, in a letter published in the August 1933 issue of *Wonder Stories. *Leiter rated stories on a scale of 1 to 10, and came to the grand conclusion that *Wonder Stories *averaged 27 percent superior to its rival, *Amazing Stories.*

When John W. Campbell, Jr. became editor of Astounding in 1937, this magazine had already taken a lead in the field, but Campbell wanted to improve both its quality and popularity. One of his first decisions was to restore Brass Tacks, a general letter department, in the November 1937 issue. Six months later he wrote, "A magazine is not an autocracy, as readers tend to believe, ruled arbitrarily by an editor's opinions. It is a democracy by the readers' votes, the editor serving as election board official. The authors are the candidates, their style and stories their platform." (April 1938:125) The first Analytical Laboratory was published in the following issue, rating the top six stories that had appeared in March. Campbell explained that the Lab was a supplement to Brass Tacks: "Since we can't print all the letters -- or even a large fraction of them -- we are going to print the results." (May 1938:160)

Other editors eventually copied Campbell's Lab. From its very beginning in 1946, the British magazine *New Worlds *has carried a readers' poll called The Literary Line-Up. In the 1950s Robert A. W. Lowndes published a poll called The Reckoning in his magazines *Dynamic Science Fiction, Future Science Fiction, The Original Science Fiction Stories, *and *Science Fiction Quarterly.*

Two readers, Walter A. Carrithers and Dennis Donahue, have attempted to expand the scope of the Analytical Laboratory. In the November 1943 issue of Astounding, Carrithers reported his analysis of 1360 Brass Tacks letters published over the previous ten years. He counted one point for each favorable mention of a story, 2.5 points for an "all time choice" rating in one of the letters, and minus one point for every disparaging opinion. Jack Williamson's novel, *The Legion of Space, *won first place for the decade, and E. E. "Doc" Smith's *The Skylark of Valeron *came in second.

Donahue's report, published in the December 1972 letter column, anticipates the analysis carried out in this article. He calculated average point scores for an accidental sample of stories by ten authors. First place went to Lloyd Biggle, Jr. on the basis of only three stories, and Donahue's analysis was not systematic enough to give reliable results. It is not good enough merely to record Lab scores and rank them or average them to get an overall rating of the authors. Before I can report my own findings, I must explain the nature of the Analytical Laboratory and show how it can be analyzed correctly.

Place | Story | Author | Points |

1 | Gulf (Part 1) | Robert A. Heinlein | 1.38 |

2 | And Now You Don't (Part II) | Isaac Asimov | 2.33 |

3 | What Dead Men Tell | Theodore Sturgeon | 3.00 |

4 | Final Command | A. E. van Vogt | 4.09 |

5 | Over the Top | Lester del Rey | 4.90 |

Figure 1: The Analytical Laboratory for November 1949.This poll rates one of the most famous issues of Analog's predecessor, Astounding Science Fiction. |

Five stories are listed in order, from the most popular to the least. In first place is installment one of *Gulf *by Robert A. Heinlein, with a point score of 1.38. Let's review how Campbell calculated this. If every reader had put Heinlein in first place, his point score would have been 1.00. Perhaps only eight people voted, five giving Heinlein first place, and three giving him second. Then Campbell would have figured the average score as follows:

Or, perhaps the vote was five hundred for first place and two hundred for second. The result would be the same. It is possible that some readers put Heinlein in third place. We do not know what the actual numbers were, but we can assume they were large.

Both in the *place *listings and in the point scores, as in the game of golf, a low number is a good rating, while a high number is bad. This seems simple enough. But there are at least four reasons why we cannot blithely add and divide the place and point scores in an overall analysis of the authors and their twenty-five hundred stories.

The first problem is that the Analytical Laboratory frequently fails to report votes on the least popular stories. In addition to the five items listed in Figure 1, the November 1949 issue also contained, "Finished, a short story by L. Sprague de Camp. We can easily add it to the list, putting it in sixth *place, *but there is no way to know how many points it received.

The second problem was mentioned by Campbell: "Not every reader letter casts votes on all the stories; thus the total number of votes cast for a particular story may not equal the total number of ballot letters." (October 1943:29) Probably, people will tend to skip stories they dislike. This means that the point scores for the least popular stories will be lower (better) than they deserve to be.

The third problem is that Campbell used an odd convention for expressing tie votes. For example, A. E. van Vogt won first place in the December 1948 issue, while Poul Anderson and Eric Frank Russell tied for second. In the Lab, Campbell gave second place to both Anderson and Russell, and awarded third place to a story by H. B. Fyfe. More properly, Fyfe should be in fourth place, since three stories got better ratings than his. Since Anderson and Russell were battling for second and third place, we should put each of them in "2.5" place. If many readers expressed tie scores the way Campbell did, then again some lower-rated stories would wind up with incorrectly good scores.

The fourth and most important problem comes from the fact that different issues contained different numbers of stories. Campbell recognized that this fact made it very difficult to compare from one issue to another. One time he commented, "The June issue carried seven stories besides the article; this means that point-score votes ranged from one to seven -- and made point scores tend to run high. That's somewhat unfair, in a way -- a third-place story or fourth-place story in such an issue has met and surpassed more competition, yet gets a tougher point score than the rearguard item in a five-story issue. Some day all things will be perfect -- and a completely fair system of reporting may be worked out." (September 1943:48) This article will use specially-designed correction formulas to defeat these four problems and make it possible to translate all scores to a single, uniform scale.

The *place* orderings, which exist for all 464 issues, can be converted to a uniform scale with a simple and mathematically sound formula. This was derived from probability logic by Toshio Yamagishi, a graduate student in my sociology department. In outline, the thinking is as follows. Suppose all twenty-five hundred stories were ranked from best to worst, in a single huge Lab. Now let Chance play the role of editor, selecting stories at random to fill the 464 issues. Finally, assume that stories within each issue were rated by a regular Lab, so we know which one is the most popular, which is second in the issue, and so on. Mr. Yamagishi pointed out that we can derive a statistical formula that lets us predict the probability that a story in a given place in an issue of given size will come from any given level in the ranking of 2500. From this rather complex mathematical expression, he derived Formula I, a very simple equation that gives the expected rank of a story. While the above logic is absurd if applied to any one actual issue, it does describe adequately the average of any randomly chosen group of issues.

X is the desired result, the story's standardized rank in a scale that can be used to compare from one issue to another. The letter P stands for the *place *the story achieved in the Lab for its issue, while m is the total number of stories in that issue, whether listed in the Lab or not. N stands for the number of steps in the standardized ranking scale, assumed to be a large number. In this article, I have let N equal 1000. Formula I divides the entire range of the ranking scale into equal parts, their number depending on how many stories appeared in the issue. November 1949 contained six stories, so Formula I divides the thousand ranking steps into sevenths. Heinlein's first-place story gets an estimated rank of 143, because 1000 x 1/7 = 143. Asimov's story, in second place, receives 286, and the others follow in order, 429, 571, 714, and 857.

What would have happened if de Camp's story had not been published, if the issue had contained only five stories? Then the thousand ranking steps would have been divided into sixths, and Heinlein's story would have received an estimated rank of 167. Like the Analytical Laboratory place and point scores, this new scale of 1000 assigns a low number to a popular story, and a high number to an unpopular one. Thus, Heinlein's story gets a better rating in an issue of six stories than in an issue of five stories. This makes perfect sense -- presumably the competition is tougher the more other stories there are in an issue. Formula I gives the following estimated ranks out of 1000 to the first-place stories in issues of from three to ten stories: 250, 200, 167, 143, 125, 111, 100, 91.

Probability logic could be applied to the *point *scores as well as to the *place *listings, deriving expected point distributions for each place in each sized issue. This would involve many tedious estimation procedures based precariously on small samples of data. I have chosen to use a cruder but still serviceable method of approximation. I start with a basic observation: The average point score for a given place in all issues of a given size is equivalent to the place number itself. For example, it turns out that the average point score for first-place items in the 82 four-item issues is 1.64. Formula I tells us that first place in a four-item issue earns an estimated rank of 200. Therefore, we can let a point score of 1.64 equal an estimated rank of 200. The average for second place is 2.24, so we let this equal 400, and so on.

This is fine for those rare stories that have exactly average scores, but what about all the others? Here I make a slightly wobbly but cogent assumption: Scores in-between can be estimated using a simple mathematical function derived from the distribution of average scores. I was prepared to try various logarithmic curves, but I was pleasantly surprised to discover that straight lines fit the data quite well. The approximation was carried out separately for each different number of stories in an issue, and involved deriving equations for what are called *regression lines *(or* trend lines*)*. *The overall error, the amount to which the straight lines missed the average scores, was only about 1.5 percent. Formula II gives the equation for converting any point score to an estimated rank in a scale with 1000 steps.

X is the desired estimated rank, while S is the story's point score, and a and b are constants derived from my regression analysis for each size of issue. Figure 2 gives the list of constants, so anyone may use this formula in their own Lab research. Of course, there are so few issues with 3, 8, or 9 stories that the estimates for these cases will be especially crude. Because real issues vary greatly in quality, Formula II will sometimes give a result less than zero or greater than a thousand. But when stories with such extreme estimated ranks are averaged in with others, these wild variations tend to wash out. Formula II is compatible with Formula I, so when a Lab fails to give a point score to a story, we can use the value from Formula I instead.

Number of Items in the Issue |
Number of Such Issues |
Constant a |
Constant b |

3 | 1 | 1.1 | 0.002 |

4 | 82 | 1.15 | 0.00265 |

5 | 202 | 1.33 | 0.00324 |

6 | 114 | 1.62 | 0.00356 |

7 | 29 | 1.48 | 0.00484 |

8 | 4 | 2.2 | 0.0033 |

9 | 1 | 1.7 | 0.005 |

Figure 2: Constants for Use In Formula II.This table lets the reader do his own Lab research using both our conversion formulas. To convert the point score of any story to our 1 000-step scale, simply plug the score and the appropriate constants from this table into Formula II. |

November 1949 was indeed an unusual issue. Despite the heavy competition, Heinlein's 1.38 score was much better than average, and it translated through Formula 11 to an estimated rank of *minus *67. Asimov gets an even 200, somewhat better than the 286 estimated by Formula I. The other scores go: Sturgeon = 388, van Vogt = 694, and del Rey = 921. If my approximation procedures are any good, Formula II gives a more precise estimate than Formula I, because it makes use of the much greater information carried by the point scores, compared with the rough place listings.

Figure 3: Honor Roll of Fifty-Three Authors.This table gives the average estimated popularity of every author who published ten or more stories ranked by the Analytical Laboratory. The best-loved authors are at the top. | |||||

Number | Average | Average | |||

of | Date | Estimated Rank | |||

Fiction | of | "Place" | "Points" | ||

Rank | Author | Items | Publication | Listings | Scores |

1 | Anson MacDonald | 10 | 1941 | 210 | 98 |

2 | Robert A. Heinlein | 25 | 1947 | 228 | 145 |

3 | E. E. "Doc" Smith | 13 | 1944 | 244 | 190 |

4 | Jerry Pournelle | 11 | 1973 | 280 | 265 |

5 | A. E. van Vogt | 59 | 1944 | 348 | 298 |

6 | Harry Harrison | 32 | 1966 | 321 | 316 |

7 | Lawrence O'Donnell | 11 | 1947 | 330 | 323 |

8 | Frank Herbert | 28 | 1963 | 381 | 329 |

9 | Poul Anderson | 67 | 1960 | 348 | 332 |

10 | Hal Clement | 29 | 1953 | 315 | 340 |

11 | Jack Williamson | 19 | 1944 | 348 | 343 |

12 | Clifford D. Simak | 39 | 1949 | 356 | 350 |

13 | Isaac Asimov | 45 | 1950 | 391 | 351 |

14 | H. Beam Piper | 20 | 1957 | 318 | 351 |

15 | Stanley Schmidt | 12 | 1972 | 363 | 362 |

16 | David Gordon | 11 | 1959 | 372 | 377 |

17 | Raymond F. Jones | 31 | 1949 | 390 | 378 |

18 | James Blish | 12 | 1956 | 380 | 386 |

19 | Gordon R. Dickson | 43 | 1965 | 414 | 387 |

20 | James H. Schmitz | 39 | 1964 | 380 | 390 |

21 | John T. Phillifent | 11 | 1968 | 410 | 391 |

22 | Eric Frank Russell | 45 | 1951 | 403 | 397 |

23 | Randall Garrett | 32 | 1961 | 372 | 405 |

24 | Walter M. Miller, Jr. | 10 | 1952 | 408 | 410 |

25 | Mack Reynolds | 48 | 1964 | 410 | 428 |

26 | Murray Leinster | 40 | 1953 | 419 | 432 |

27 | Lester del Rey | 24 | 1944 | 442 | 433 |

28 | Lewis Padgett | 35 | 1945 | 437 | 434 |

29 | Fritz Leiber | 14 | 1946 | 452 | 439 |

30 | L. Ron Hubbard | 23 | 1944 | 443 | 441 |

31 | E. B. Cole | 15 | 1957 | 428 | 456 |

32 | Theodore Sturgeon | 23 | 1945 | 423 | 457 |

33 | L. Sprague de Camp | 27 | 1946 | 456 | 460 |

34 | Katherine MacLean | 10 | 1959 | 427 | 472 |

35 | Robert Silverberg | 15 | 1961 | 472 | 480 |

36 | Malcolm Jameson | 28 | 1942 | 520 | 510 |

37 | George 0. Smith | 34 | 1949 | 529 | 520 |

38 | Christopher Anvil | 73 | 1964 | 556 | 542 |

39 | Nathan Schachner | 16 | 1939 | 548 | 564 |

40 | Ross Rocklynne | 16 | 1942 | 555 | 579 |

41 | Theodore L. Thomas | 10 | 1962 | 619 | 595 |

42 | Robert Chilson | 12 | 1970 | 583 | 620 |

43 | Algis Budrys | 22 | 1957 | 640 | 636 |

44 | Jack Wodhams | 24 | 1969 | 610 | 644 |

45 | A. Bertram Chandler | 19 | 1952 | 608 | 647 |

46 | Walt & Leigh Richmond | 11 | 1965 | 634 | 667 |

47 | Lee Correy | 10 | 1956 | 710 | 669 |

48 | H. B. Fyfe | 20 | 1953 | 657 | 681 |

49 | P. Schuyler Miller | 12 | 1942 | 717 | 683 |

50 | Harry Walton | 11 | 1942 | 742 | 723 |

51 | W. Macfarlane | 14 | 1967 | 725 | 732 |

52 | Lawrence A. Perkins | 11 | 1969 | 725 | 747 |

53 | Frank Belknap Long | 11 | 1945 | 829 | 805 |

A glance at this big table shows that Robert A. Heinlein, "Dean of Science Fiction Writers," is in second place. What author could possibly be more popular than Heinlein? The answer is: Heinlein himself! "Anson MacDonald" was one of Heinlein's pen names. There are other pen names on the list. "David Gordon" is a pen name of Randall Garrett. "Lawrence O'Donnell" and "Lewis Padgett" are both pseudonyms for the collaboration of Henry Kuttner and C. L. Moore. "Clement," "Anvil," and "Correy" are also pen names, but their owners are not represented by other names on the list. There are several surprises in Figure 3, but I will leave these discoveries to the reader. There is much to contemplate and debate in the table, but I will turn to the question of how mere length influences popularity of works of fiction.

Figure 4: Popularity of Serial Installments.The first installment of a serial tends to be more popular than the second, third, or fourth installment. Perhaps, readers forget plot and character details over the month's gap between episodes, and others may find it confusing to begin reading in the middle of a story. The chart also shows that full-size novels of three or four installments are more popular than shorter novels, even in the first installment. | |

Campbell commented on the length factor several times. "One of the problems inherent in science fiction is that each story actually is a brief glimpse of an alien world-scene. The longer the story, the more chance the author has to give a feel of reality -- a texture of living fabric -- to his world-picture. Result: a longer story, all things -- and authors! -- being equal, will have more satisfying effect for the reader." (June 1956:72) Of course, it may simply be that readers best recall those stories that took longest to read, subconsciously multiplying the enjoyment experienced per page times the number of pages to arrive at a total impression. Perhaps this is partly true, but Figure 4 shows something more subtle. First installments of two-episode stories and short novels rank much lower than first installments of three-episode and four-episode novels. When the readers rate these opening installments, they have not yet read the concluding parts of each work. Apparently, long fiction has a special quality that emerges even in the first few chapters. When an author writes a long novel he probably invests more effort in planning and characterization, so that even the first part of a long novel conveys more vivid images than an equally long segment of a shorter work.

Another time, Campbell explained: "Generally, the longer a story is, the more chance the author has to work out his background ideas, characters, and plotting. Serials generally take first place, primarily because the author can do a better job. Unlike here-and-now-stories, science fiction must describe even the common things of life -- life in the story environment. More space gives more chance for that. The result is that there are very few long-remembered, "classic" short stories, a few novelettes, but many much-mentioned serials." (July 1946:122) To test this idea on all kinds of fiction, I tabulated place distributions for all fiction published in the 187 five-story issues that contained no Lab ties. Figure 5 gives the results.

Figure 5: Percentage of Four Kinds of Fiction AchievingEach "Place" In 187 Five-Story Issues. Long fiction has a tremendous advantage over short fiction. This table summarizes Lab ratings of 935 stories and serial installments, showing that the shortest works almost never achieved high popularity. | ||||

Serial | Short | Short | ||

Place | Installments | Novels | Novelettes | Stories |

1 | 70% | 51% | 20% | 2% |

2 | 18% | 40% | 42% | 5% |

3 | 10% | 9% | 24% | 22% |

4 | 2% | 0% | 11% | 33% |

5 | 0% | 0% | 3% | 38% |

Total | 100% | 100% | 100% | 100% |

Number of Items | 145 | 35 | 294 | 461 |

The pattern is quite regular. Serials beat out short novels which surpass novelettes which win over short stories. Indeed, the short stories are crammed into the last three places. Figure 5 shows that the length factor is really very powerful. Since length of fiction makes such a difference, we should reconsider Figure 3 and its* *estimates of popularity for the authors. Some authors may write huge, dull novels that get good ratings simply because they are big and, therefore, memorable. Other authors may create marvelous jewels of short stories, which have less impact on the swift-eyed readers. Figure 3 is entirely valid, so long as we understand that it measures the over-all impact of each author rather than the quality of writing page-for-page. We need an alternative estimate of popularity that removes the powerful influence of length of fiction.

Figure 6: Popularity Map of Fifty-Three Authors, Correcting for Length of Fiction. Each circle represents one author. Open circles are authors who held their positions or even lost ground when we switched to a length-corrected measure of popularity. Solid circles represent authors that gained five or more places in the ranking.
| |

The vertical dimension of Figure 6 puts the best-liked authors at the top, and the least-liked at the bottom. Authors on the right side wrote a high proportion of short fiction, while authors on the left specialized in long works. Open circles represent writers who lost ground from the ranking in Figure 3, or barely held their ground. Solid circles are authors that rose five or more places in the ranking. As expected, the authors that rose significantly in the new ranking tended to write a good deal of short fiction.

An unfortunate effect of thirty-eight years of Analytical Laboratories may have been to downgrade short stories in favor of vast epics, thereby slighting the genius of some very fine authors. Close examination of Figure 6 will help redress the balance. The most spectacular rise was 27 places, achieved by Malcolm Jameson who went from 36th to 9th. Lester del Rey zoomed up 21 places, while other big gainers were Gordon, Russell, Walter Miller, Leiber, Leinster, Padgett, MacLean, Sturgeon, Silverberg, Anvil, and Correy. Each of them gained ten or more places in the ranking. Four authors dropped more than twenty places: "Doc" Smith, Harrison, Clement, and Piper. Despite the fact that he seldom wrote short stories, MacDonald-Heinlein did not budge from first-and-second place.

Our final use of Lab statistics will be to chart the changing popularity of three authors throughout their Astounding-Analog careers. I have chosen A. E. van Vogt, Poul Anderson, and Isaac Asimov because they are the best known of the most prolific writers. I arranged each man's stories from earliest to latest so we could see the trends over time. If I just graphed the raw data, we would have a bewildering tangle of zigzags, so I did two things to smooth the curves out. First, I used the length-corrected popularity estimates on which Figure 6 was based. If we did not correct for length of fiction, the line on the graph would hop up and down wildly as each author switched back and forth from long novels to short stories. Second, I further damped out short-term variations by calculating seven-point moving averages. A "moving" average does just what the name implies -- it moves. Each point does not really represent the popularity of a single story, but of that story averaged in with the three that came before it and the three that come after it. Thus, the height of the line at X = 4 is the average score for stories 1 through 7. The height at X = 5 is the average for stories 2 through 8, and the height at X = 6 is the average for stories 3 through 9. Because we need seven stories for each average, we can't calculate values for the first three and last three stories by each author. Figure 7 shows the careers of van Vogt, Anderson, and Asimov.

Figure 7: The Careers of van Vogt, Anderson, and Asimov. These charts are like stock market graphs, showing the ups and downs in the Astounding-Analog careers of three of the best-known and most prolific science fiction writers.
| |

We can read these lines just like the ones on stockbrokers' graphs indicating the ups and downs in the stock market. Van Vogt's graph shows a tragic pattern. He begins very high, and rises slowly to a marvelous crest that begins to turn downward at the end of 1943. A gradual decline steepens into a precipitous fall, halted only briefly, that drops into a chasm in 1946. A recovery over the next two years restores only a third of the original loss, and van Vogt fades until his last story in 1950.

Anderson's pattern is quite different. It depicts a stalwart writer ready to battle back from adversity. He starts in the late 1940s just at the 500 average, and quickly rises to the 300 level. He holds a plateau, until suffering a terrible slump around 1958. He struggles back up to his former popularity, then slips back to begin a steady rise that continues until the end of the period covered by the Lab.

We see yet a third pattern in Asimov's graph. He starts at a very high level around the year 1940, drops quickly, then recovers to the 200 level. A steady decline sets in, taking him down below 600 in 1954. His final recovery is not. as simple as it appears on the graph. After publishing in Astounding-Analog quite regularly, Asimov was completely absent from its pages from 1956 to 1968, and only his last two stories, in 1972 and 1976, received really good ratings. The overall trend of Asimov's line is* *downward. Just as van Vogt vanished from Astounding after years of decline, so did Asimov, devoting himself instead to a splendid career of popular science fact writing. We cannot say for sure that Asimov was driven out of science fiction by a declining popularity, and only he can tell us if he experienced his career in this way. In fact, it takes a close reading of the Labs to discern the negative trend. The estimates reflected in Figure 3, which have not been adjusted for length of fiction, do not show it, but display a very shallow rise. The reason is that Asimov shifted from short to long fiction over his career. Sixty-four percent of his first 22 Astounding pieces were short stories, but only 18 percent of the last 22. While Asimov's short stories were rated higher than most other authors' shortest works, his long fiction was rated near the average for novels and novelettes. One of the most remarkable facts about Asimov's career is that he has established himself as possibly the most famous contemporary science fiction writer, despite the fact that most of his fiction was written decades ago** **and did not receive consistently favorable ratings.

Bainbridge, William Sims, *The Spaceflight Revolution, *Wiley-Interscience, New York, 1976.

Bainbridge, William Sims and Murray Dalziel, "New Maps of Science Fiction," *Analog Yearbook,* Baronet, New York, 1978, pages 277-299.

Bainbridge, William Sims and Murray Dalziel, "The Shape of Science Fiction," *Science-Fiction Studies, *Vol. 5, July 1978, pages 164-171.

McGhan, Barry, *Sciencefiction and Fantasy Pseudonyms, *Misfit Press, Dearborn, Michigan, 1976.

Rogers, Alva, *A Requiem for Astounding, *Advent, Chicago, 1964.

Tuck, Donald H., *The Encyclopedia of Science Fiction and Fantasy, *Volumes 1 and 2, Advent, Chicago, 1974, 1978.