President’s Column: How Members Can Help Improve the Industry’s Public Image
Notice bibliographique
Résumé
Editor’s Note: This is a summary of the April episode of the President’s podcast. We encourage you to listen to the episode to hear the full conversation. In this podcast episode, I am joined by Paige McCown, senior manager of communication and energy education, to discuss the importance of how SPE engages with external stakeholders to help improve the industry’s public image, particularly through programs like energy4me. I start the episode by emphasizing how the industry’s public image is a critical concern for our future, and it’s a common question among members about what SPE can do to help. Although environmental scrutiny of the industry has always been present, it has become more pronounced with the increased focus on climate change and emissions. The energy industry has made many positive impacts across the world, from providing energy for almost everything we do to producing everyday products and conveniences. I also believe that the industry is best positioned to solve today’s energy challenges. However, two main problems related to our public image hinder our ability to meet these challenges: our ability to attract the best talent, and our ability to attract investments in technology and innovation. The discussion turns to ways to change public perception. I review some of the topics discussed at the Presidents Panel that I participated in at IPTC 2024. These include how engaging students at a young age and making them aware of the benefits of the industry helps change the narrative at an early age. Also, it is important to engage teachers, guidance counselors, and communities in promoting our positive aspects. The conversation moves to how SPE is equipping its members to engage in these efforts. I highlight SPE’s energy4me program which provides an exploration and production curriculum and hands-on activities to teach the science behind the industry. To accompany the program, SPE worked with DK Publishing to publish the Oil and Natural Gas book, available in nine languages, which helps convey the importance of the industry and provides talking points for members to use in their communities. SPE deploys the program through workshops at key events, virtual workshops, and the Energy4me Ambassador program. Sections and chapters across the globe are active in this program, so in 2022 SPE created the Corporate Ambassador program. Companies like ExxonMobil, EOG Resources, and Aramco Americas participated in the program. The program can help some companies meet their corporate responsibility and community outreach goals. I also spend time discussing how local sections and chapters are using the program in their communities. We highlight various initiatives including STEM education programs, workshops for teachers and guidance counselors, and outreach events like Family Science Day. The Calgary section YPs organize an annual Family Science Day, aimed at educating students about oil and gas and putting on fun experiments.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,007 | 0,029 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,006 | 0,002 |
| Communication savante | 0,012 | 0,009 |
| Science ouverte | 0,002 | 0,004 |
| Intégrité de la recherche | 0,011 | 0,020 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,066 | 0,029 |
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.
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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».