On the Problem of Dependent People: hyperbolic discounting in Atlantic Canadian island jurisdictions
Bibliographic record
Abstract
Prince Edward Island's Economics, Statistics and Federal Fiscal Relations Division's 33rd Annual Statistical Review reports the total value of 2006 fish landings was CAD $166.6 MM. This paper discloses a preliminary finding that the actual total value of fish landings for 2006 was approximately CAD 416.5 MM. Furthermore, this discourse submits that this entrenched systemic error has been consistently generated for all 33 years that the Annual Statistical Review has been published. Moreover, this systemic error creates a ripple-effect and promotes bias through all relative natural resource valuations. This significant conjecture is presented within an institutional context which serves as the foundation for this error generation, including other errors associated with The Problem of Induction and The Tragedy of the Commons. Within this broad context, this paper focuses upon deficient resource valuation methods, especially as they relate to dependency and valuation errors. Our analysis contrasts the failure of fishery management amongst dependent Canadian islanders, and the relative success of fishery management amongst independent Icelandic islanders. The possibilities that independent people enjoy higher levels of rationality, efficiency, happiness, economic sustainability, Darwinian fitness, resource holding power, and, are thus, ceteris paribus, less likely to commit errors associated with The Problem of Induction are taken into consideration. Likewise, consideration is given to the notion that dependent people are more likely to exhibit irrational behaviour, develop deeper dependencies, and to contribute to a wide array of maladaptive behaviours, such as those which exacerbate The Tragedy of the Commons.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.062 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.007 | 0.009 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".