Una definició de talent: orientadora per a la seua gestió a l’empresa i base per a la RSU
Bibliographic record
Abstract
L’objectiu d’aquest article és delimitar el significat i abast del concepte talent en el món de l’empresa, com a punt de partida perquè les organitzacions implicades en el desenvolupament sostenible de la societat i l’economia del país –especialment les universitats i les empreses– complisquen amb la responsabilitat que tenen enfront de la societat en la qual influeixen. Pretén que els stakeholders implicats la prenguen com el punt de partida per a construir una nova manera de fer i de treballar en el desenvolupament de les persones en les empreses, per tant, en les comunitats i la societat en general. Aquest article beu de la literatura acadèmica especialitzada i publicada en revistes d’impacte entre els anys 1987 i 2018 sobre el significat del concepte talent en les organitzacions i, sobre la responsabilitat social de les organitzacions que influeixen en la seua definició.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.029 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".