Enlazando actitudes entre el medio ambiente y los mercados de productos naturales
Bibliographic record
Abstract
En este articulo se explora como las actitudes de los consumidores respecto al medioambiente influyen en su disposicion a pagar (DAP) una prima adicional por adquirir productos que posean una certificacion medioambiental. Se hace una revision de la literatura existente que valida el supuesto de que mayores actitudes en pro del medio ambiente llevan a tener una mayor DAP hacia productos que cuenten con una certificacion medioambiental. Tales actitudes, de tipo unidimensional, raramente han sido desagregadas a fin de conocer distinciones respecto de dicho tema. Se busca elaborar una teoria acerca de como la DAP se ve influenciada por tres distintos tipos de actitudes respecto al medioambiente, lo cual se basa en las categorias desarrolladas por Gladwin, Kennelly y Krauze [1995]: tecnocentrismo, ecocentrismo y sustentabilismo. Se evaluan las hipotesis mediante encuestas personales anonimas aplicadas a 306 consumidores en Mexico. Por medio de un analisis de correspondencia para determinar la DAP y escalas para medir la actitud ambientalista a traves de las variables definidas por Gladwin, Kennelly y Krauze [1995], se encuentra evidencia que validan nuestras hipotesis. Se concluye con una discusion acerca de las implicaciones que tienen los hallazgos sobre la teoria, la practica y las politicas referidas a los segmentos de consumidores ambientalistas
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".