Adquisición de negocios con opciones de compra : Canada
Bibliographic record
Abstract
El presente trabajo busca confirmar el comportamiento racional de los individuos encargados de ejecutar las compras de negocios empresariales, es decir, si las empresas a la hora de adquirir o fusionarse con otras compañías, efectivamente lo hacen como supone la teoría. Y la teoría nos dice que el mejor medio de pago para realizar la compra de un negocio es a través de un Earnout. Para esto, se recurrió a la basa de datos estadísticos DataStream que nos permitiera verificar la forma en que las empresas negocian las adquisiciones en el mundo real. De aquí se tomaron 37231 fusiones y adquisidores realizadas en Canadá entre los años 1981 y 2016, y del total de observaciones se tuvieron solo 413 que hacían uso de esta opción ren la respectiva transacción.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".