Pourquoi ce travail est dans la base
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Notice bibliographique
Résumé
Yoshi Takei faced a major career challenge as he headed towards a meeting with his team. His team experienced a significantly higher rate of layoffs than comparable teams throughout the organization. Takei was a Japanese-American manager of a team of network engineers that worked in a Fortune 100 telecommunications company, Everlast, based in the Northeast region of the U. S. Promoted to a management position after excelling technically as a software engineer, he and his fast-paced engineering team provided critical network builds for major government and business clients. Takei knew his team was overworked, overstressed, and beaten down, but he had more bad news to deliver. Downward pressure forced him to cut one more person. His employees worked more than 60 hours per week already and eliminating another employee was likely to seriously damage whatever morale was left in his group. The economy was in the doldrums. Everlast, driven by quarterly earnings, had experienced a number of reductions in force (RIFs) since 2008. His challenge after the series of layoffs was how to rebuild trust and credibility with his team as part of his efforts to rejuvenate his flagging managerial career at Everlast. Mr. Takei's Team and the RIF Process for Networking Engineers Takei once oversaw a team of 12 employees, but due to quarter-over-quarter downsizing over the past year-and-a-half, his team now consisted of just seven engineers. Other managers who ran the same function in other states made it through most of the corporate force reductions without losing a single employee; whereas, Takei administered the busiest territory, but was forced to make painful cuts every quarter. Gamesmanship and politicking tended to play a significant role in the reduction in force (RIF) process at Everlast, or so Takei believed. These activities were abhorrent to Takei who believed that engaging in these activities were beneath him. His team had a huge network build to complete within the next eight weeks for a major customer, so he needed everybody focused on the network build because the regional executive management team had placed the project under close scrutiny. On the surface, Takei knew that RIFs at Everlast were determined by assessing candidates for downsizing according to the following criteria: area of company where employee worked, productivity, teamwork, quality, customer satisfaction, and attendance. From Takei's experience as engineering team manager, he believed the ultimate criteria for retention of employees ultimately depended on the grandstanding and political behavior of their manager at RIF meetings. Bob Bazile, Takei's direct supervisor, served as head of the Regional Executive Committee and was also head of the Networking Engineer RIF committee. Takei was also aware that Bazile had told him that Takei was not his first choice to head up the network engineering team Takei now led. Bazile's first choice was Joe Archilazzi, a personal friend and golfing buddy of Bazile. While a decent engineer with a knack for developing contacts and networks both inside and outside Everlast, Archilazzi had a reputation for cutting corners in order to uphold the deals he made. Bazile's choice of Archilazzi was overruled by the Everlast Corporate Management Development Board that had responsibility for succession planning and was the ultimate arbiter of appointments at this level. …
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,008 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle