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Record W2255301193 · doi:10.1667/0033-7587-17.2.147

Personal Consumption Rates for Canada: Differentiated By Family Size and Income Level Using Survey of Household Spending (SHS) 2000 Data

2004· article· en· W2255301193 on OpenAlexaboutno aff
Cara L. Brown

Bibliographic record

VenueJournal of Forensic Economics · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsSpousePersonal consumption expenditures price indexDamagesConsumption (sociology)Personal injuryDemographic economicsPersonal incomeWrongful deathPosition (finance)EconomicsBusinessFamily incomeConsumer spendingActuarial scienceLabour economicsLawEconomic growthSociologyPolitical scienceFinance

Abstract

fetched live from OpenAlex

Canada’s leading legal scholar on the subject of injury torts, Ken CooperStephenson, wrote in Personal Injury Damages in Canada (1996) that the object of each province’s Fatal Accidents Act1 is to “restore the defendants to the financial position they would have been if the deceased had lived” (p. 419).2 A substantial body of common law has developed whereby Canadian judges3 have attempted to decide personal consumption rates (PCRs) to assign to the decedent when making an award to the surviving family,4 but few (or possibly none) have considered evidence on the influence of family income on PCRs. Generally speaking, Canadian courts have considered all sources of the decedent’s income interrupted by his/her death;5 the surviving spouse’s income level when making the award, and the number of dependents and span of dependency. They have rejected the notion characterizing the type of marriage to assess emotional loss for survivors who lose the benefit of spending money on his/her partner or providing services.6

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.197
Threshold uncertainty score0.428

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.201
GPT teacher head0.353
Teacher spread0.153 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations1
Published2004
Admission routes1
Has abstractyes

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