Relations de service : nouveaux usages, nouveaux usagers
Bibliographic record
Abstract
Les relations de services ont fortement evolue ces dernieres annees sous le triple impact tout d'abord, des exigences et attentes des clients-usagers ; ensuite, par la mobilisation croissante de nouvelles modalites d'interaction via des technologies innovantes et, enfin, par le recours a de nouvelles formes de mobilisation des ressources humaines (gestion des competences, evolution du travail et des organisations, nouveaux modes de management.). Cet ouvrage a pour objectif de constituer un livre de reference sur l'emergence de nouveaux usages et de nouveaux usagers dans les relations de services, desormais au centre du developpement economique des pays occidentaux. Sur la base d'un eclairage ouvert et pluridisciplinaire issu de la psychologie du travail, de l'ergonomie, des sciences de gestion, mais aussi de la sociologie du travail, ce livre se propose de donner d'une part, un apercu des differentes dimensions et evolutions qui se jouent au sein de la relation de services et, de fournir d'autre part, les concepts et methodes necessaires a l'analyse et a la comprehension des phenomenes etudies. Par ses approches plurielles et complementaires, cet ouvrage interessera un large public : Etudiants de Master (en psychologie, ergonomie, GRH, sociologie du travail, management, marketing, economie des services.) Praticiens d'entreprise privee et publique (cadres et dirigeants, praticiens en formation continue, psychologues du travail, responsables RH, specialistes du marketing, responsables methodes et organisation. ) Enseignants-chercheurs et formateurs dans les domaines concernes.
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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 | 0.013 | 0.066 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.006 | 0.016 |
| Scholarly communication | 0.018 | 0.046 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.019 | 0.005 |
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".