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Record W1560923170 · doi:10.1561/100.00014068

Useless Prevention vs. Costly Remediation

2015· article· en· W1560923170 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueQuarterly Journal of Political Science · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural risk and resilience
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsEconomic rentPrincipal (computer security)Agency (philosophy)LimitingPrincipal–agent problemPrivate information retrievalMicroeconomicsBusinessAction (physics)Computer securityEconomicsRisk analysis (engineering)Public economicsComputer scienceEngineeringFinance

Abstract

fetched live from OpenAlex

I model the dynamic agency relationship underlying prevention. In each period, a principal sets a budget for an agent that has private information about a problem, which the agent can direct to solving the problem or divert into rents. Problems are persistent and rectifiable: they randomly generate observable disasters until enough resources have been committed to solving them. I characterise the principal’s equilibrium trade-off between (a) preventing disasters while squandering transfers in informational rents to agents facing trivial problems and (b) limiting transfers and remediating costly disasters that eliminate agents informational advantage and prove the need for action.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.877
Threshold uncertainty score0.123

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.028
GPT teacher head0.276
Teacher spread0.248 · 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