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Record W4413095367 · doi:10.11647/obp.0477.06

6. An Economic Model to Capture Effects of Historical Trauma

2025· book-chapter· en· W4413095367 on OpenAlexaff
Mukesh Eswaran

Bibliographic record

VenueOpen Book Publishers · 2025
Typebook-chapter
Languageen
FieldSocial Sciences
TopicCulture, Economy, and Development Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsIndigenousResource (disambiguation)Resource allocationPsychological traumaPhenomenonHistorical traumaPsychologyCognitive psychologyEconomicsPsychotherapistEpistemologyComputer scienceEcologyManagementBiology

Abstract

fetched live from OpenAlex

Chapter 6 sets out an economic model that offers one approach to analysing the effects of historical trauma. Consulting evidence on the link between historical trauma and psychological pain, it extends the model from Part I to incorporate the endogenous responses of individuals to historical trauma. Formal analyses of resource allocation typically ignore the phenomenon of pain, which is particularly relevant to North American Indigenous communities. Consequently, the model in this chapter is particularly oriented towards examining the resource allocation effects of persistent pain, the response to which takes the form of pain alleviation. The chapter derives the equilibrium in a hypothetical Indigenous community experiencing shared historical trauma.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.017
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0170.002

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 head0.031
GPT teacher head0.291
Teacher spread0.260 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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