MétaCan
Menu
Retour à la cohorte
Enregistrement W4242655064 · doi:10.1111/1541-4329.12051

Food Science Education Publications and Websites

2015· article· en· W4242655064 sur OpenAlexaboutno aff
Jim Bird

Notice bibliographique

RevueJournal of Food Science Education · 2015
Typearticle
Langueen
DomaineAgricultural and Biological Sciences
ThématiqueUrban Agriculture and Sustainability
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésLibrary scienceColumn (typography)ConversationSociologyEngineering

Résumé

récupéré en direct d'OpenAlex

Jim Bird I started writing this column in July 2006, 5(3). This, my 35th column will be my last, as I am retiring as the head of the Science & Engineering Center, Fogler Library, Univ. of Maine. Over the years I have corresponded with some of you. I have tried to find interesting papers and websites to include. I hope you have found something useful in this column. I want to thank the editors of the Journal of Food Science Education that I have worked with: Wayne Iwaoka, Grady Chism, and Shelly Schmidt. All have been very supportive. I would also like to thank Amanda Ferguson, Associate Director, IFT Scientific Journals, with whom I have interacted over the years. She has kept me focused on my deadlines and has helped in many ways. Starting with JFSE 14(2), Robert S. (Pat) Allen will be writing this column. Pat is Associate Professor of Library Administration, Agriculture, Consumer, and Environmental Sciences (ACES) Librarian at the Univ. of Illinois at Urbana-Champaign. He can be reached at allen2@illinois.edu. Thank you all. Jim Bird (Jim.Bird@umit.maine.edu) The authors write about the implementation of organic permaculture food gardens at 2 public primary schools in Johannesburg, South Africa. Garden lesson plans were taught at both schools. The purpose of the school gardens and the assessment was to look at the diet and nutrition of the children and “…to broaden the conversation regarding the challenges and opportunities of school food gardens for health education and as a part of the holistic model of the health promoting school approach.” (p. 286). The authors discuss the potential benefits of school gardens and limitations of their project. The authors choose 10 existing community gardens and evaluated them “…in order to better understand design strategies, patterns, and landscape elements that lead to effective community gardens.” (p. 2). Schematics of each garden is included. Using their evaluation, recommendations are made on various design elements including layout, paths, gathering spaces, seating, and compost areas. A literature review was done using standard literature databases such as PubMed, Science Direct, Proquest databases, and others. A list of the search terms is provided. Based on criteria which are presented in the article, 19 peer-reviewed papers and 4 grey-literature programs were identified. Two very detailed tables summarize the 23 selected papers and programs. The following is reported for each: Intervention type and strategies, target group and sample size, duration, food literacy areas addressed, theoretical models or basis, evaluation methods, and outcomes. The authors note that “…findings of this review suggest that there have been few specifically designed effective and innovative food literacy programmes for this target group.” (p. 168). There is an extensive discussion section and reference list. In an innovative use of Radio Frequency Identification (RFID) technology, visitors to Spitalfields City Farm in inner east London can approach plants and using a watering can with RFID, can hear the plants talk “…about their history, how to care for them as well as eat them, and also their medicinal and health properties.” (p. 460) Preliminary findings from visitor responses show that The Talking Plants provide a learning opportunity and that the technology employed is easy to use and accessible “…particularly for people with visual impairments.” (p. 461) The authors note in their conclusion that: “Future work on The Talking Plants will involve Internet of Things technologies to connect the plants to the web, by creating a smart watering-can which can access a web-based repository of community-based knowledge.” (p. 462) Through the use of lectures and lab experiments/demonstration by professors and chefs, the authors describe 2 courses developed at Harvard Univ. and Univ. of California, Los Angeles (1 each) for undergraduate nonscience majors. These courses fulfill the general education requirements at each university. They detail the science concepts taught by lectures, chef classroom demonstrations, and student laboratory experiments. These concepts include phases of matter, elasticity and gels, diffusion, thermal energy transfer, and microbes. Review of student final projects indicates the courses are a success. Bair KC, Sinley RC, Albrecht JA. 2013. Food safety education cube for Native Americans. RURALS: Review of Undergraduate Education in Agricultural and Life Sciences 8(1): Article 1. Available from: http://digitalcommons.unl.edu/rurals/vol8/iss1/1/. Accessed Oct 27, 2014. Benson MC. 2014. Exploring extension involvement in farm to school program activities. J Extension 52(4): Article #4FEA4. Available from http://www.joe.org/joe/2014august/a4.php. Accessed Oct 27, 2014. Blackburn ML, Bruhn CM, Miller LS, Ganthavorn C, Ober B. 2014. Seniors, and their food handlers and caregivers, need food safety and nutrition education. Calif Agr 68(1–2):30–37. Available from http://californiaagriculture.ucanr.edu/landingpage.cfm?article=ca.v068n01p30&fulltext=yes. Accessed Oct 27, 2014. Christner MA and Cotugna N. 2014. Evaluation of a school food pantry program. J Hung Environ Nutr 9(3):362–371. Doi: 10.1080/19320248.2014.908451. Hertzman JL, Kitterlin M, Farrish J, Stefanelli J. 2011. The effect of food safety education and work experience on knowledge, attitudes, and practices of university students. J Hosp Tour Educ 23(1):18–27. Doi: 10.1080/10963758.2011.10696995 Husted S, Gutierrez JV, Ramirez-Corona N, Lopez-Malo A, Palou E. 2014. Multidimensional assessment of creativity in an introduction to engineering design course. 121st ASEE Annual Conference & Exposition, Indianapolis, IN, June 15–18, 2014. Paper ID #8789. Available from: http://www.asee.org/public/conferences/32/papers/8789/view. Accessed Oct 27, 2014. Husted S, Ramirez-Corona N, Lopez-Malo A, Palou E. 2014. Creativity and its assessment in a design and development of food products and processes course. 121st ASEE Annual Conference & Exposition, Indianapolis, IN, June 15–18, 2014. Paper ID #8966. Available from: http://www.asee.org/public/conferences/32/papers/8966/view. Accessed Oct 27, 2014. Husted S, Ramirez-Corona N, Lopez-Malo A, Palou E. 2014. A creative experience for chemical, food, and environmental engineering students in a material balances course. 121st ASEE Annual Conference & Exposition, Indianapolis, IN, June 15–18, 2014. Paper ID #8787. Available from: http://www.asee.org/public/conferences/32/papers/8787/view. Accessed Oct 27, 2014. Karrebæk MS. 2014. Rye bread and halal: Enregisterment of food practices in the primary classroom. Lang Comm 34:17–34. Doi: 10.1016/j.langcom.2013.08.002. King H. 2013. Food safety management – implementing a food safety program in a food retail business. Food microbiology and food safety series. New York: Springer. 130 p. Kurtz HE, Wood J. 2014. Stone Soup: Photo-elicitation as a learning tool in the food geography classroom. J Geogr Higher Educ 38(4):546–556. Doi: 10.1080/03098265.2014.958657. Maijala P, Närvä M, Pasila A. 2014. Farm-to table concept: How the industry and commerce are integrated to the academic educational system. Agron Res 12(2):673–680. Available from: agronomy.emu.ee/vol122/2014_2_37_b5.pdf. Accessed Oct 28, 2014. Malleswari K, Patil D, Sridhar G, Prasad BN. 2014. Role of food processing training and exposure visits in empowering the rural women community. Prabandhan: Indian J Manage 7(5):17–25. Mou Y and Lin CA. 2014. Communicating food safety via the social media: The role of knowledge and emotions on risk perception and prevention. Sci Commun 36(5):593–616. Doi: 10.1177/1075547014549480. Murphy M, Ballam R, Coe S. 2014. Supporting the communication of EC-funded food, agriculture and biotechnology research through a European educational toolkit for schools: The development and design process. Nutr Bull 39(3):276–283. Doi: 10.1111/nbu.12103. Nowatschin EA. 2014. Educational food landscapes: Developing design guidelines for school gardens. Univ. of Guelph. M.L.A. Thesis. 142p. Available from: https://atrium.lib.uoguelph.ca/xmlui/handle/10214/8057. Accessed Oct 27, 2014. Nunez GH, Kovaleski AP, Darnell RL. 2014. Formal education can affect students’ perception of organic produce. Hort Technol 24(1):64–70. Schilling JK. 2013. A comparison of participant gains in attitude and behavior after experiencing a food safety curriculum in traditional and computer delivered environments. Mississippi State Univ. Ph.D. Dissertation. 91 p. Thippaiah A, Allagh KP, Murthy GV. 2014. Challenges in developing competency-based training curriculum for food safety regulators in India. Indian J Community Med 39(3):147–155. Doi: 10.4103/0970-0218.137151. Warner A, Callaghan E, de Vreede C. 2013. Promoting sustainable food and food citizenship through an adult education leisure experience. Leisure/Loisir 37(4):337–360. Doi: 10.1080/14927713.2014.906176. Wight RA. 2014. The agroecological-educator: Food-based community development. Community Dev J 49(2):198–213. Doi: 10.1093/cdj/bst038.

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)0,002
score de la tête « metaresearch » (Gemma)0,011
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Synthèse · Signal consensuel: aucune
Score de désaccord entre enseignants0,647
Score d'incertitude au seuil0,504

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,011
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0060,013
Études des sciences et des technologies0,0040,001
Communication savante0,0150,006
Science ouverte0,0010,003
Intégrité de la recherche0,0020,003
Charge utile insuffisante (le modèle a refusé de juger)0,6470,657

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 Opus0,034
Tête enseignante GPT0,271
Écart entre enseignants0,237 · 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.

Devis d'étudeSans objet
Domainenon disponible
GenreSynthèse

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
Publié2015
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueJournal of Food Science EducationMême sujetUrban Agriculture and SustainabilityTravaux en français237 207