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Enregistrement W2324042643 · doi:10.1097/01.hj.0000324431.83523.55

Students say, despite technology, human element is key

2005· article· en· W2324042643 sur OpenAlexaff
Donald J. Schum

Notice bibliographique

RevueThe Hearing Journal · 2005
Typearticle
Langueen
DomaineEnvironmental Science
ThématiqueAcademic Research and Education Studies
Établissements canadiensPricewaterhouseCoopers (Canada)
Organismes subventionnairesnon disponible
Mots-clésAudiologistElement (criminal law)Medical educationHumanismFoundation (evidence)PsychologyEngineering ethicsPedagogyMedicinePolitical scienceEngineeringHearing lossLawAudiology

Résumé

récupéré en direct d'OpenAlex

All great professions are guided by the seasoned, but driven by the young. Audiology is no different. For the past decade, Oticon, Inc., has striven to do what it can to enhance the educational process for graduate students in audiology. Among other initiatives, we have hosted a camp every summer for the past 7 years in Keystone, CO. Focusing on advanced technology and clinical practice in amplification, we have supported student research and offered an audiologic lecture series at universities across the country. This year, in celebration of Oticon's 100-year anniversary, we have joined forces with the Copenhagen-based Oticon Foundation to offer scholarships to 100 graduate students in audiology. As part of the application process for these $600 awards, the students were required to write a 500-word essay in response to the question, “Why is a people-oriented profession still relevant in an increasingly technology-oriented society?” Given Oticon's People First philosophy, we were interested in seeing how the next generation of professionals view their role in an era in which hearing aid technology is evolving so rapidly. The results provide testament that the future of audiology is in the hands of talented and insightful individuals who will continue to respect our humanistic heritage. Of course, all of the applicants pointed to the importance of a strong relationship between the patient and the professional, and they agreed that technology should never be viewed as a substitute for the patient-audiologist relationship. However, a handful of students demonstrated an important insight into the role of the professional in the relationship between the professional and technology. They recognized the value that technology can offer patients with hearing loss, but also perceived that this value can only be fully realized via the intervention of the professional audiologist. HUMAN NEEDS DRIVE TECHNOLOGY Technology does not advance for its own sake. Rather, technologic advances are driven by human needs. Therefore, technology should not be viewed as de-humanizing. Quite the opposite. Technology offers the user the opportunity to reach his or her greatest potential. Or, as Rosalinda Baca of the University of Colorado said, “Society is not losing its interest in people by being technology driven; rather, technology is a key to address the increasing needs of people.” However, in our field, someone must be the link between technology and the patient. Alexandra Vetrovski of Central Michigan University noted, “Technology makes people curious. That's how it gets invented and why it continues to be used. Yet not everyone in the world is gifted in understanding…so the unknowledgeable turn to the knowledgeable.” Technologic advances continually open a broader and broader range of potential solutions. But these solutions must be tailored to the needs of the end user. The professional plays the vital role in ensuring that this takes place. Virginia Ramachandra of Wayne State University explained, “The labor-saving aspect of technology serves to enhance and highlight the people-oriented nature of the profession, while the advent of new technologies creates areas of possibility. Professionals must adapt the technology to the goals of the consumer.” “There is no doubt that technology will continue to advance our society and allow jobs to become easier and more efficient, but technology can take us only so far,” cautioned Emily Bondus of Purdue University. She added, “People have to step in and make technology understandable and usable for others. There is a value-added partnership between humans and technology [that] will continue to change our world.” As we move into the future, the role of the professional as the interface between technology and the patient should only be expected to increase. Erin McAlister of the University of Maryland put it this way: “The increasing prominence of technology in our society only enhances the need for people-oriented professions to facilitate successful relationships between human needs and the potential benefits of technology.” Our profession will continue to be challenged to produce new professionals who possess both the technical expertise to understand new technology as it is developed and the skill to unlock the potential of these new solutions for the patient. It is clear that these scholarship-winning students have been positively influenced by their professors and clinical instructors. Already they have seen that there is an important role for technology in the treatment of hearing loss, and they have also realized that the full potential of this technology can be achieved only when it is managed within a larger, patient-centered process. We congratulate these students and wish them well as they prepare to enter their professional lives. We are proud to be part of their development.

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.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,006
score de la tête « metaresearch » (Gemma)0,014
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,039
Score d'incertitude au seuil0,130

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0060,014
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0050,014
Communication savante0,0120,012
Science ouverte0,0010,008
Intégrité de la recherche0,0060,011
Charge utile insuffisante (le modèle a refusé de juger)0,0390,029

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.

Tête enseignante Opus0,042
Tête enseignante GPT0,378
Écart entre enseignants0,335 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2005
Routes d'admission1
Résumé présentoui

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