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Record W3203477145

Rejecting Word Worship: An Integrative Approach to Judicial Construction of Insurance Policies

2021· article· en· W3203477145 on OpenAlexaff
Erik S. Knutsen, Jeffrey W. Stempel

Bibliographic record

VenueSSRN Electronic Journal · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicLegal Systems and Judicial Processes
Canadian institutionsQueen's University
Fundersnot available
KeywordsContext (archaeology)Insurance policyLegislative historyStatutory interpretationLawSupreme courtLegislationInterpretation (philosophy)Political scienceLaw and economicsEconomicsSociologyHistoryPhilosophyLinguistics
DOInot available

Abstract

fetched live from OpenAlex

Litigation over insurance coverage is really a quest for meaning: Does the insurance policy cover the loss at issue? Construing the insurance policy, courts are attempting to give legal effect to what the document purports to command. But what were the intentions and expectations of insurer and insured? Do those intentions even matter? Or is only the written text of the policy relevant to the coverage result? Courts approaching these questions typically frame the interpretative choice as one of strict textualism versus a more contextual, functionalist approach. In many, perhaps even most situations, text and context align to create an “easy” case. If a factory is sued for contaminating a neighborhood pond, the absolute pollution exclusion almost certainly applies. If builder’s bulldozer cuts an underground powerline, the insurer cannot avoid coverage by labeling the mishap as excluded faulty work. But in more uncertain circumstances, a court’s choice of methodology often changes the result, with significant consequences for risk management and victim compensation. Despite the departure from strict adherence to textualism signalled in the Restatement (Second) of Contracts in 1981, courts typically continue to embrace a highly textualist approach in contract interpretation cases, including insurance cases. Strict textualism continues to be one of the core orthodoxies of American law and dispute resolution, even though both modern cognitive science and practical experience have shown its limits. Undue reverence for text abounds even when inapt. Deviation from textual orthodoxy is often unfairly condemned as result-oriented judicial activism or judicial legislation that undermines the predictability and consistency to which law aspires. In our view, departures from strict textualism – especially (but not only) in insurance cases – are mistreated as heretical when they are in fact comprehensive, insightful, and helpful in vindicating the apt function of insurance and other agreements. A more expressly integrative harnessing of the indicia of contract term meaning does not excessively empower judges relative to legislatures, executives, and private parties but instead permits courts to be helpful in ensuring that statutes, contracts, and in particular insurance policies function in a manner consistent with the intent, purpose, and operation of these writings and the objectives they represent. Courts in our view need not be cabined by excessive textualism in order to “stay in their lane” relative to other branches and the decision-making preferences of the parties but can adopt a broader, more integrative approach to construction without violating traditional norms regarding judicial role. The integrative solution is not radical but realistic and should enjoy greater, expressly acknowledged, judicial favor.

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)0.026
metaresearch head score (Gemma)0.035
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.026
Threshold uncertainty score0.138

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.035
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0050.002
Science and technology studies0.0090.060
Scholarly communication0.0210.021
Open science0.0050.008
Research integrity0.0070.011
Insufficient payload (model declined to judge)0.0050.001

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 head0.017
GPT teacher head0.300
Teacher spread0.283 · 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 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

Citations22
Published2021
Admission routes1
Has abstractyes

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