Towards an Evolutionary Understanding of the Current Global Socio-economic Crisis and Restructuring: From a Conjunctural to a Structural and Evolutionary Perspective
Bibliographic record
Abstract
The current global socio-economic crisis and restructuring reshapes the terms of study of the global dynamics as a whole. A new generation of interdisciplinary socio-economic research on the matter in question seems to be progressively emerging in international literature.Against this background, it gradually emerges the understanding, that any attempt to interpret the individual contemporary socio-economic phenomena, which relate to the crisis and the attempt to restructure globalization, can only be inadequate and ineffective, since it fails to fully approach the current dynamics of globalization in synthetic, holistic terms.In this direction, new interpretative approaches seem to intensify interpenetration and conceptual syntheses between the different fields of socio-economic sciences, in an increasingly unified perspective, by extensively "borrowing" –in a direct and indirect way– methods and theoretical "lenses" derived from system science, chaos theory, and evolutionary economics.In the depth of this methodological rearrangement, according to the position put forward in the following paper, it is crucial that an effort is made to move from a conjunctural to a structural perception of the crisis. Ultimately, the great challenge for the field of study of global dynamics nowadays is the transition from the methodological principles of the traditional mechanistic interpretative method to a coherent and integrated evolutionary socio-economic perspective.
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 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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.024 |
| Scholarly communication | 0.011 | 0.021 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".