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The patent paradox – New insights through decision support using compound options

2011· article· en· W2005834850 on OpenAlexafffund
David H. Goldenberg, Jonathan D. Linton

Bibliographic record

VenueTechnological Forecasting and Social Change · 2011
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIntellectual Property and Patents
Canadian institutionsUniversity of Ottawa
FundersSocial Sciences and Humanities Research Council of CanadaTelfer School of Management, University of OttawaUniversity of OttawaRensselaer Polytechnic Institute
KeywordsEnforcementPatent trollValue (mathematics)BusinessProfit (economics)Patent infringementPatent officePatent analysisEconomicsIndustrial organizationLaw and economicsPublic economicsIntellectual propertyPatent lawMicroeconomicsLawComputer sciencePolitical science

Abstract

fetched live from OpenAlex

By considering the patent from the perspective of a compound option it is possible to offer useful insights into what a patent does, when it is worth patenting, and the effects of changes to patent regulation and enforcement in terms of maximizing economic and societal benefits. A paradox exists because stronger patent laws with longer durations allow greater profit to the inventor, but strong and long patent protection discourages related innovation as the protection for the underlying technology becomes broader and duration is longer. Through the demonstration that under current regulation the net present value of a sample patentable invention must be a little over half a million dollars ($556,000) at the time of patent filing, insight is offered into when it is economically advisable to patent. The effect of changes to patent regulation can also be rapidly assessed using this technique. Consequently, the compound option provides value to policy makers for decision support in assessing the impact of changes to patent policy and to inventors and patent attorneys on assessing whether it is economically rational to patent.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.639
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 studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.642
GPT teacher head0.287
Teacher spread0.355 · 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 teacher head, not a consensus.

Study designTheoretical or conceptual
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

Citations14
Published2011
Admission routes2
Has abstractyes

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