O consumo na hipermodernidade: o superendividamento como consequência da oferta irresponsável do crédito
Bibliographic record
Abstract
RESUMOO artigo tem o objetivo analisar a relação entre hipermodernidade e consumo, com ênfase na oferta irresponsável do crédito e no superendividamento. Para tanto, por intermédio de estudo bibliográfico, analisa o problema do desenvolvimento da hipermodernidade com a busca da felicidade associada ao consumo na perspectiva de uma sociedade líquida, além de como a cultura do ter que estimula o superendividamento. Por fim, chega-se o entendimento de que o consumidor tem que ser um elemento protagonista nas relações de consumo com o escopo de garantir a autonomia da vontade no ato negocial.PALAVRAS-CHAVEHipermodernidade. Consumidor. Autonomia da Vontade. Superendividamento. ABSTRACTThe present article aims to analyze the connection between hypermodernity and consumption, with an emphasis on the irresponsible credit supply and over-indebtedness. Therefore, through a bibliographical study, it analyzes the problem of the development of hypermodernity with the search for happiness associated with consumption in the perspective of a liquid society, in addition to how the culture of “owning” stimulates super indebtedness. Finally, it arrives at the understanding that the consumer has to be a protagonist element in consumer relations with the scope of guaranteeing the autonomy of the will in the negotiating act.KEYWORDSHypermodernity. Consumer. Autonomy of Will. Over-indebtedness.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 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".