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Record W7032976116

The Ouroboros Model : Solving the Paradox of Abundance and Decline

2025· article· en· W7032976116 on OpenAlexaboutno aff

Bibliographic record

VenueKTH Publication Database DiVA (KTH Royal Institute of Technology) · 2025
Typearticle
Languageen
FieldHealth Professions
TopicAthletic Training and Education
Canadian institutionsnot available
Fundersnot available
KeywordsCommodificationPoliticsFertilityWork (physics)Space (punctuation)Socioeconomic statusValue (mathematics)InequalityLimit (mathematics)
DOInot available

Abstract

fetched live from OpenAlex

This thesis investigates the structural roots of fertility decline in developed economies. It argues that two forces of space and time play a central role in shaping reproductive decisions. Employing political economy, sociology, and demography, the study examines how rising land values and overextended temporal demands limit family formation in developed societies. Using Canada as a case study, the thesis combines empirical data with theoretical insight. A concept of ‘sealevel rent’ is introduced to illustrate how economic pressures engulf the landless, thereby suppressing reproductive capacity. Regional contrasts such as Nunavut suggest that fertility thrives where land is less commodified and time is less regulated. The thesis concludes that reversing demographic decline will require more than policy incentives, but that it demands structural transformation. It proposes land value taxation and a reorganization of work week as potential reforms, arguing that only by rethinking how societies allocate space and time can they restore the socioeconomic conditions necessary for demographic resilience.

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)0.006
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 score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.003
Scholarly communication0.0030.005
Open science0.0020.003
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0190.001

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 head0.047
GPT teacher head0.393
Teacher spread0.346 · 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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Same venueKTH Publication Database DiVA (KTH Royal Institute of Technology)Same topicAthletic Training and EducationFrench-language works237,207