Obstáculos de la investigación contable – una mirada desde la epistemología tradicional
Bibliographic record
Abstract
El presente documento es una respuesta a la pregunta de investigación ¿qué obstáculos están presentes en la investigación contable? La respuesta tendrá como marco de referencia la teoría contable de mayor aceptación en las instituciones de formación profesión (corriente principal), signada por la influencia del triángulo de la epistemología tradicional de Kuhn, Popper y Lakatos. El análisis contable ha estado mediado intrínsecamente por las tendencias monistas, dualistas y pluralistas; racionalistas e irracionalistas; externalistas e internalistas; objetivistas y subjetivistas; positivistas y normativistas y anglo-euro-centristas e independentistas, situación que ha convocado a reflexionar si dichas dicotomías constituyen una oportunidad de avance o un obstáculo para el desarrollo científico de este milenario saber. La contabilidad no es un saber teóricamente monolito, por el contrario, está representado por la confluencia no pacífica de diferentes corrientes de pensamiento que, entre colisiones y coaliciones, relacionan entre el antagonismo y la complementariedad para formar ese conjunto de saberes teóricos y prácticos que rigen el que hacer del profesional contable.
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 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 | 0.015 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.007 | 0.035 |
| Scholarly communication | 0.026 | 0.021 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 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; 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".