Consciential Intelligence in Peruvian Adults Before the COVID-19 Pandemic
Bibliographic record
Abstract
Objective: To describe the profile of Consciential Intelligence (CI) in Peruvian adults before the COVID-19 pandemic occurs. Theoretical Framework: Concepts and theories are provided that underpin the study and provide a solid basis for understanding the subject matter and context of the research. Method: Cross-sectional study of 415 adult participants in the province of Ica-Peru. Data collection was carried out by means of an online survey using the Consciential Intelligence Scale and a questionnaire with general variables. Results and Discussion: The majority of the participants presented an unhealthy CI profile; better CI scores were revealed by women, health worker, evangelical religion, young life stage and higher education. Results vary according to existential thinking and transcendental awareness in practice. It is recommended that this modality of intelligence be cultivated and developed so that it can flourish to the fullest. Research Implications: CI is presented as an alternative to recover human values in a community with patterns and paradigms typical of a dystopian society. Originality/Value: CI is a recently coined term to refer to Howard Gardner's ninth multiple intelligence. A construct that has regained relevance in the current times of crisis of conscience because of its relationship with virtuous behaviour.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".