Développement de l’expertise des usagers via les TIC : quels enjeux pour les travailleurs des relations de services ?
Bibliographic record
Abstract
Les services immatériels et relationnels occupent une part de plus en plus importante dans l’économie et le développement de la croissance. L’objectif principal de cet article est d’analyser les effets des technologies d’information (E.services : E.banking ou E.administration) dédiées aux usagers dans les relations de services ultérieures en face à face avec les agents. Deux études ont été réalisées : dans le secteur privé (banques) et dans le secteur public (mairie).Dans les faits, les expertises acquises par les usagers produisent de nombreux effets sur l’activité des professionnels : développement de compétences, autonomie, implication, mais aussi un ensemble d’engagements pour réguler les différentes modalités d’intensification de la charge de travail (apprentissage, comportements d’adaptation) ainsi que leur impact sur la santé (stress).
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 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".