MétaCan
Menu
Back to cohort
Record W4387397935 · doi:10.1353/nin.2023.a903328

Last Time Out; Big League Farewells of Baseball's Greats by John Nogoski (review)

2023· article· en· W4387397935 on OpenAlexvenueno aff
Chad S. Wise

Bibliographic record

VenueNine · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicAmerican Sports and Literature
Canadian institutionsnot available
Fundersnot available
KeywordsLeagueHistoryArt historyClassicsArt

Abstract

fetched live from OpenAlex

Reviewed by: Last Time Out; Big League Farewells of Baseball's Greats by John Nogoski Chad S. Wise John Nogoski. Last Time Out; Big League Farewells of Baseball's Greats. Essex, CT: Lyons Press, 2022, 310 pp. Paperback, $22.95. Attend any Major League Baseball game in any city, and you'll find fans wearing jerseys of not only current stars, but legends as well. Having grown up near Cincinnati, Ohio, I can remember seeing jerseys of the Big Red Machine: Johnny Bench, Pete Rose, Dave Concepcion, and Tony Perez. We put our stars on pedestals, not for their off-field lives, but for the way they played the game. They were as close to being gods as any human could imagine. However, as I look back at some of my Reds heroes, I can recall how their names and fanfare started fading away year after year. They were replaced by younger, faster, and stronger players. In John Nogoski's book, Last Time Out; Big League Farewells of Baseball's Greats, he shares with baseball fans of all ages how the careers of so many great players came to conclusions, some bowing out gracefully, while others were sent packing by an unforgiving media and fanbase. Nogoski's book covers forty-five baseball players from the last century, describing the stories behind each of their final farewells. Some, like Ted Williams retired at the top of their game. In a career that spanned twenty-one years, Williams wasn't without controversy. His relationship with the media was certainly strained. However, his talking was done on the field. He hit 521 total home runs (putting him in third place at the time, behind Babe Ruth and Jimmie Foxx, and good for twentieth place on the home run list as of today), hit nearly 2,000 runs batted in, and had nearly 2,700 hits. He also lost some of his prime playing years while serving as fighter pilot in World War II and Korea. The most amazing statistic for Williams involves his home runs. In his final year of 1960, he started the season with a home run. By the last game of the year, to a small crowd of just about 10,000 people at Fenway Park that held three times as many fans, he did the unthinkable. At the age of forty-two, he hit a home run in his last at bat as a player. As he entered the dugout after his final home run, the fans and players cheered him out of the dugout for a "curtain call." That was not, however, how Williams played the game. He simply looked at Jack Fisher, pitcher for the Baltimore Orioles, and motioned for him to pitch to the next batter. To even casual fans of baseball, Game Six of the 1975 World Series between Boston and Cincinnati seemed like it happened yesterday. Who hasn't seen the video of Boston's catcher, Carlton Fisk, motioning his arms at the ball he hit to stay fair? The ball did stay fair, and the Red Sox went on to win the [End Page 140] game and force a seventh game. The home run Fisk hit was probably his single most memorable event in a career that lasted twenty-four years, catching 2,226 games and hitting 351 home runs (79). As the years piled up, things started to change for Fisk. The new ballplayers began, in his words, "cheating the game," not running out singles and not playing at full speed. Nogoski describes an incident between Fisk and New York Yankees outfielder Deion Sanders in 1990: Sanders hit a short ball that would be an easy play at first. But instead of running it out, Sanders jogged to first. This infuriated Fisk, who yelled, "Run it out, you piece of s***!" and caused the umpire to step in and diffuse the situation (76). This was a sign that Fisk's "moral crisis" with younger players was becoming a real issue. As Nogoski writes, "At 45, his (Fisk) sermons were mostly falling on deaf ears already plugged with headphones and diamond earrings. Fisk felt as much of an outsider as a rookie" (78...

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.104
Threshold uncertainty score1.000

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.1050.001

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 head0.018
GPT teacher head0.222
Teacher spread0.205 · 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; both teacher heads agree on what is shown here.

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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueNineSame topicAmerican Sports and LiteratureFrench-language works237,207