Bibliographic record
Abstract
В статье рассматриваются экосистемные основания концепции социальной резилиентности как теоретико-методологического подхода к исследованию способов преодоления обществом глобальных вызовов. Концепция резилиентности (англ. resilience) была предложена канадским экологом К.С. Холлингом. Изучая развитие экологических систем в меняющихся условиях окружающей среды, Холлинг вывел две характеристики резилиентности: это (1) способность системы поглощать внешние воздействия и сопротивляться им, сохраняя исходные параметры, и (2) величина воздействий, которые может выдержать система, прежде чем она перейдет в иное состояние. На основе системного подхода в начале XXI в. концепция резилиентности стала применяться для анализа способности общества или социальных групп справляться с последствиями стихийных природных бедствий. В статье показано, что центральную роль в сохранении социальной резилиентности играют адаптация, т.е. способность людей разрабатывать и внедрять меры реагирования на меняющиеся внешние условия, и трансформируемость, т.е. способность общества преобразовывать структуру социума и находить новые траектории развития. Сделан вывод о необходимости дальнейшего научного осмысления содержательных и теоретико-методологических оснований концепции резилиентности для ее последующего использования в теоретических и прикладных исследованиях способов преодоления последствий глобальных вызовов. The article examines the ecosystem foundations of the concept of social resilience as a theoretical and methodological approach to studying the ways in which society can overcome global challenges. The concept of resilience was proposed by the Canadian ecologist C.S. Holling. When studying the development of ecological systems in changing environmental conditions, Holling derived two characteristics of resilience. Those are (1) the ability of a system to absorb external influences and resist them while maintaining the initial parameters and (2) the magnitude of the impacts that a system can withstand before it passes into a different state. Based on the systems approach, at the beginning of the 21st century, the concept of resilience began to be used to analyze the ability of society or social groups to deal with the consequences of natural disasters. The article shows that adaptation, i.e. the ability of people to develop and implement measures to respond to changing external conditions, and transformability, i.e. the ability of society to transform its structure and find new development trajectories, play a key role in maintaining social resilience. The conclusion is made that further understanding of the substantive and theoretical-methodological foundations of the concept of resilience is needed for its subsequent use in theoretical and applied research on ways of overcoming the consequences of global challenges.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.024 | 0.006 |
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".