MétaCan
Menu
Back to cohort
Record W285944451

The Sweet Sixteen: The Journey That Inspired the Canadian Women's Press Club

2012· article· en· W285944451 on OpenAlexaboutno aff
Patrick S. Washburn

Bibliographic record

VenueJournalism & Mass Communication Quarterly · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsClubSubject (documents)Government (linguistics)HistoryMedia studiesLawSociologyPolitical scienceLibrary scienceMedicinePhilosophy
DOInot available

Abstract

fetched live from OpenAlex

Holland, Max. Leak: Why Mark Felt Became Throat. Lawrence: University Press of Kansas, 2012. 302 pp. $29.95. When Bob Woodward and Carl Bernstein's All the President's Men was published in 1974, immense speculation immediately surrounded the identity of Deep Throat, the anonymous government official who had provided them with invaluable information and guidance for their Watergate stories. They steadfasdy refused to identify him and said they would only do so after he died. That all changed, however, in May 2005 when Mark Felt, a high-ranking FBI official when the Watergate break-in occurred, admitted in a Vanity Fair article that he had been their secret source. Leak: Why Mark Felt Became Throat is written by Max Holland, who is editor of the website Decoded, a contributing editor to the Wihon Quarterly and The Nation, and the author of a book about the aftermath of President John Kennedy's assassination. He became interested in the subject of his current book in 2007 when the Watergate-related papers of Woodward and Bernstein were sold to the University of Texas. As he says in his acknowledgements, I thought any newly opened papers were likely to contain at least a few new insights into an old crisis. As it turns out, this book has one major insight: the reason Felt leaked information to Woodward, frequently in underground garage meetings at night, as well as other journalists, most notably Sandy Smith of Time magazine. Before publication of Holland's book, three reasons were posited for Felt helping the press with the Watergate story: he wanted to expose the unlawful behavior of President Richard Nixon and those around him in the White House before the office of the presidency was irrevocably harmed; he wanted to protect the FBI from being manipulated and controlled by the White House; and he was bitter at the White House for naming L. Patrick Gray rather than him the interim director of the FBI after J. Edgar Hoover died in 1972. In addressing the why question in Felt's behavior, Holland did extensive research. This included sixty-six interviews, not only with Woodward, Bernstein, Ben Bradlee, and Howard Sussman of the Washington Post, but also with Nixon insiders such as Charles Colson and John Dean. He also examined twenty-nine oral histories, documents in three presidential libraries (Nixon, Jimmy Carter, and Ronald Reagan) as well as at the National Archives, and material that he obtained from the FBI through a Freedom of Information Act request. The end result is a highly entertaining, compelling treatise by Holland that Felt's leaks to the press were designed solely to make him the next full-time FBI director. …

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.088
Threshold uncertainty score0.642

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.005
Science and technology studies0.0580.017
Scholarly communication0.0220.007
Open science0.0020.006
Research integrity0.0060.007
Insufficient payload (model declined to judge)0.0550.008

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 head0.033
GPT teacher head0.270
Teacher spread0.237 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueJournalism & Mass Communication QuarterlySame topicCanadian Identity and HistoryFrench-language works237,207