MétaCan
Menu
Back to cohort
Record W235776249 · doi:10.21236/ada394765

Antipersonnel Landmine Policy for the New Administration

2001· report· en· W235776249 on OpenAlexaboutno aff
Fritz W. Kirklighter

Bibliographic record

Venuenot available
Typereport
Languageen
FieldSocial Sciences
TopicMilitary and Defense Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAdministration (probate law)TreatyPolitical scienceForeign policyCriticismLawFace (sociological concept)Sign (mathematics)National securityPublic administrationSociologyPolitics

Abstract

fetched live from OpenAlex

In the face of severe criticism from most of the world's leaders, President Clinton on 17 September 1997 refused to sign the Ottawa treaty, declaring: 'As Commander-in-Chief, I will not send our soldiers to defend the freedom of our people and the freedom of others without doing everything we can to make them as secure as possible. There is a line I simply cannot cross, and that line is the safety and security of our men and women in uniform'. His own internal struggle with this issue was demonstrated during an interview weeks before President Clinton left office during which he said he 'bitterly regretted that the U.S. did not sign the land mine treaty in December 1997, and that it is one of his bitterest regrets of the last eight years'. The President of the United States is responsible for balancing the military needs and humanitarian concerns of the nation. Land mine policy will be a challenging issue for the Bush administration, testing the president's military and foreign policy. This paper will probe the anti-personnel land mines (APL) issue, seeking to review our approach to the Ottawa treaty, current U.S. policy, and present recommendations on future APL policy for the Bush administration.

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)0.002
metaresearch head score (Gemma)0.005
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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.232
Threshold uncertainty score0.461

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.002
Scholarly communication0.0080.004
Open science0.0010.001
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0200.002

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 head0.117
GPT teacher head0.424
Teacher spread0.308 · 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
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
Published2001
Admission routes1
Has abstractyes

Explore more

Same topicMilitary and Defense StudiesFrench-language works237,207