O Contexto Econômico e Ambiental Contemporâneo e as Novas Perspectivas em Gestão: Republicação de artigo em homenagem ao professor Omar Aktouf // The Economic and Environmental Contemporary Context and the New Perspectives for Management: Republishing an article in honor of Professor Omar Aktouf
Bibliographic record
Abstract
Omar Aktouf, intelectual argelino, professor titular da HEC Montréal, membro fundador do centro de humanismo, gestão e globalização e do conselho científico da ATTAC Québec (Action citoyenne pour la justice fiscale, sociale et écologique) nasceu em 1944 na Argélia. Morreu em 2 de abril de 2025 em Montreal, Quebec. Tivemos o privilégio e a honra de receber o professor Aktouf para uma temporada acadêmica na Universidade Federal do Ceará, ocasião em que ministrou várias palestras na área da Psicologia Organizacional e Administração, além de contribuir com publicações e pesquisas locais. Naquela altura publicou um texto autoral na Revista de Psicologia da UFC intitulado O “CONTEXTO ECONÔMICO E AMBIENTAL CONTEMPORÂNEO E AS NOVAS PERSPECTIVAS EM GESTÃO”, no qual apresenta (em suas próprias palavras): “o resultado das minhas reflexões atuais sobre o panorama da economia mundial e, principalmente, do que muito se fala acerca da economia, da administração, da psicologia organizacional e temas correlatos”.
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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.017 | 0.032 |
| Scholarly communication | 0.020 | 0.007 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.011 | 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".