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Record W2553040017 · doi:10.21273/hortsci.35.3.513e

668 The ASHS/People-To-People Mission to China

2000· article· en· W2553040017 on OpenAlexaboutno aff
Donald N. Maynard

Bibliographic record

VenueHortScience · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Law and Aviation
Canadian institutionsnot available
Fundersnot available
KeywordsBeijingChinaDelegationFriendshipPolitical scienceEconomic growthPublic administrationGeographyEnvironmental protectionSociologyLawSocial science

Abstract

fetched live from OpenAlex

The Citizen Ambassador Program was initiated in 1956 when President Dwight D. Eisenhower founded “People to People.” His vast perspective as a military and governmental leader led him to believe that individual citizens reaching out in friendship to the people of other nations could make a significant contribution to world understanding. From 14–28 Aug. 1998, ASHS took part in the “People-to People Mission to China.” Our delegation was composed of six ASHS Members and two guests. Delegates were from Canada and Brazil and the United States. After meeting in Los Angeles for a final briefing, the delegation departed for Hong Kong, where we immediately boarded a flight to Beijing. Our China experience began in Beijing, then on to Hangzhou, Shanghai, Guangzhou, and Hong Kong. All of these locations are in the densely populated eastern portion of China. (China has approximately the same area as the United States, but it has 1.25 billion people compared to only 270 million in the U.S.) Our time at each location was about equally divided between professional and cultural activities. Our Chinese horticultural colleagues were enthusiastic and well-trained. As in the United States, the quality of the facilities and the equipment varied somewhat among locations. Operating funds, never sufficient for research and maintenance of facilities, commonly were supplemented by sale of horticultural products.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.118
Threshold uncertainty score0.235

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0060.002
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0220.003

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 head0.010
GPT teacher head0.300
Teacher spread0.291 · 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
Published2000
Admission routes1
Has abstractyes

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