Antropología de la Comunicación y Cultura Empresarial: El Caso Cascades
Bibliographic record
Abstract
El presente artículo intenta establecer, sobre la base de una investigación empírica realizada en la empresa Cascades que las "culturas organizacionales" que realmente llegan a forjarse e instalarse no se logran como resultado de una acción deliberada y artificial de "ingeniería". Estas culturas sólo pueden construirse mediante un compartir ante todo cosas concretas. Los elementos claves en este proceso son: el compartir al máximo aspectos de la vida de la organización, como las utilidades, la información, las decisiones, los locales, los materiales, etc. y la aplicación en los hechos de un discurso y una filosofía empresarial que deliberadamente rompa con las tradiciones administrativas más cimentadas, mediante el privilegio absoluto de lo oral, la apertura y la transparencia, la confianza y la autonomía generalizadas, el respeto y la valoración del empleado, la ausencia de puestos de supervisión y control, la cercanía y disponibilidad de los directivos, etc.* Omar Aktouf y Michel Chrétien. L 'A nthropologieie la communicationet la culture d'entreprise: le cas Cascades. Ponencia en lnternational Conference on Organizational Symbolism, Universidad del Québec. Montreal, junio de 1986.
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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.012 | 0.014 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.027 | 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".