Estudios empíricos sobre la industria de los ordenadores personales
Bibliographic record
Abstract
Esta tesis consiste en una serie de estudios empiricos sobre la industria de los ordenadores personales basados en datos de 8 paises americanos (Argentina, Brasil, Canada, Chile, Colombia, Estados Unidos, Mexico y Peru) entre 2005 y 2007, y se compone de 3 capitulos. En el primer capitulo se analizan estadisticamente las principales caracteristicas de esta industria. El segundo capitulo aporta una vision panoramica del escenario competitivo, ofrece una estimacion de la demanda y del poder de mercado por grupos de empresa, e interpreta la logica economica de los cambios observados en Latinoamerica a raiz del proceso de migracion hacia la portabilidad. El tercer capitulo representa una contribucion a la literatura sobre el analisis retrospectivo de las fusiones. En el se estudia el impacto sobre precios del anuncio y la fusion Acer – Gateway, ocurridos durante 2007 y que permitio a estas firmas convertirse en el tercer proveedor mundial de ordenadores personales.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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; both teacher heads agree on what is shown here.
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".