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Record W4328029944 · doi:10.1177/00027162231155040

Loss of Life and Labor Productivity: The Canadian Opioid Crisis

2022· article· en· W4328029944 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueThe Annals of the American Academy of Political and Social Science · 2022
Typearticle
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsProductivityCapital (architecture)EconomicsHuman capitalOpioidValue of lifeValue (mathematics)Demographic economicsDemographyMedicineGeographyEconomic growthSociologyStatistics

Abstract

fetched live from OpenAlex

Opioids were declared a public health emergency in British Columbia, Canada, in 2016, and from that year through 2021, 29,894 Canadians lost their lives to opioid overdoses. More than two-thirds of those victims were employed in the five years prior to their deaths, and this study aims to quantify their lost productivity to the Canadian economy. We apply two human capital model variants in our analysis, projecting forward the future economic output of individuals who died from opioids, from their deaths to what would have been their eventual retirements, based on the industries in which they were employed. The total estimated productivity loss to Canada is at least $8.8 billion, with the equivalent “value of statistical life” calculations an order of magnitude higher; these are based on estimates of the amount of money that individuals would pay to avoid death. Our results challenge the notion that the opioid crisis predominantly affects unproductive members of society.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.851
Threshold uncertainty score0.996

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 studies0.0010.007
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 head0.047
GPT teacher head0.360
Teacher spread0.313 · 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