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Record W4294315057 · doi:10.1353/nin.2022.0028

The Baseball 100 by Joe Posnanski

2022· article· en· W4294315057 on OpenAlexvenueno aff
Willie Steele

Bibliographic record

VenueNine · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicAmerican Sports and Literature
Canadian institutionsnot available
Fundersnot available
KeywordsLeagueStadiumArt historyArtFootballGeorge (robot)HistoryMedia studiesSociologyLawPolitical science

Abstract

fetched live from OpenAlex

Reviewed by: The Baseball 100 by Joe Posnanski Willie Steele Joe Posnanski. The Baseball 100. New York: Avid Reader Press, 2021. 869 pp. Cloth, $40.00. If there is anything baseball fans love more than the sound of a wood bat hitting a ball or the smell of hot dogs at the ballpark, it’s arguing. Fans will argue over whether a pitch was a ball or a strike. They’ll argue over which stadium is the best in the majors. They’ve been known to argue about which minor league team has the greatest mascot. And they have even argued over which suffered the most before finally winning a recent World Series, the Cubs or the Red Sox. In the introduction to The Baseball 100, commentator George F. Will begins by saying, “Baseball fans are an argumentative tribe” (1). And somewhere, probably in Cleveland, I can hear a fan respond, “No we aren’t!” If you are a reader who is looking for Joe Posnanski’s latest book, The Baseball 100, to solve any arguments, don’t get your hopes up. If you are looking for [End Page 142] a book to start a lot of arguments, more often than not between the reader and the author, you won’t be disappointed. And if you are looking for a book that reminds you why baseball has the greatest collection of characters in sports history, you’ve come to the right place. The book is, as its title indicates, Posnanski’s list of baseball’s top one hundred players. The chapters were originally written as individual articles over a hundred-day stretch when they were published on the Athletic website. Rather than simply relying on advanced statistics, and there are certainly plenty of those to go around, Posnanski incorporates the roles players played in the game’s rich (and often complicated) history, interesting sidebars about their lives, and elements of their lives and abilities that made them stand out from the thousands of players who did not make the list. In his introduction to the collection, the author recounts a story of when former Major League Baseball (MLB) commissioner Bud Selig called him to dispute the rankings that had appeared on the website. Rather than defending his choices, Posnanski readily admits to the reader, “You will have bones to pick, too” (6). He knows you’ll disagree with the list, and he’s okay with it. Unlike nearly every other book, The Baseball 100 is missing a table of contents, making it impossible for readers to jump ahead to the players they are most interested in or to see what players Posnanski has ranked and in what order. But instead of being put off by this tool, this reader enjoyed not knowing who was coming next in the book until he had finished the current chapter. (I will admit, however, that I skipped to the end to see who he’d ranked number one.) Perhaps the most interesting aspect of this book is the variety of players Posnanski chose for his list. The first chapter, or the hundredth best player, is (spoiler alert!) Ichiro Suzuki. And the last chapter, or the number one player to have ever played baseball, is (another alert!) Willie Mays. In between, there are players from MLB and players from the Negro Leagues, players from the Deadball Era and the modern era, players who are identifiable by a single name (“Babe”), and others whom you have most likely never heard of. Posnanski’s list is as much a tutorial of baseball’s history as it is a reminder of what makes its most iconic players so memorable. Throughout the book Posnanski gives readers glimpses into those players with whom he became acquainted in his career as a sportswriter, explains the memorable moments associated with many of the players, and debunks some long-standing myths associated with others in the game. The result is a compilation of players that is part biography, part statistical analysis, part mythology, and all baseball. Readers will find themselves appreciating the complexity in each chapter while arguing “Yes, but what about . . .” multiple times. [End Page 143] Some of the lengthier chapters are...

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.222
Threshold uncertainty score0.779

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.2220.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.186
Teacher spread0.179 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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