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Record W2588822870 · doi:10.21273/hortsci.39.4.838d

Rapid Response Educational Efforts: Keeping Cooperative Extension Ahead of the Curve

2004· article· en· W2588822870 on OpenAlexaboutno aff
William T. Hlubik, Nicholas Polanin, Madeline Flahive DiNardo, Richard Weidman, David Smela, James Marko, Sean Convery

Bibliographic record

VenueHortScience · 2004
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicDiverse Educational Innovations Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPacePresentation (obstetrics)Service (business)CurriculumPublic relationsComputer scienceMultimediaSociologyPolitical scienceBusinessMarketingGeographyMedicinePedagogy

Abstract

fetched live from OpenAlex

Today's fast paced and technology-enriched lifestyles require that many traditional educational seminars and workshops be transformed into “sound bites” of “edu-tainment” if Extension is to keep pace with clientele needs for specific and timely information that's useful and straight to the point. To remain a viable source of timely research-based information, Extension can stay ahead of this curve by utilizing today's technology to inform and educate the public on current issues or outbreaks. This presentation will highlight two such cases where technology delivery systems were utilized to maximize audience size and create an informed public in as short amount of time as possible. Public Service Announcements (PSA's) televised over New Jersey's Public Broadcasting Service (PBS), New Jersey Network (NJN), addressed water conservation and landscape issues during the recent northeastern drought. The potential viewing audience is over eight million people, including all of New Jersey and parts of Pennsylvania, Delaware, New York, and Connecticut. The second case study will highlight a fully interactive CD-ROM on the Asian Long Horned Beetle (ALB) that was created within 12 months of the pest's discovery in Jersey City, N.J. This CD-ROM, containing curricula, PowerPoint presentations and evaluative tools, is currently being used throughout the northeast and in Canada for the most recent infestation of ALB. Filming for both Rapid Response efforts was done with a Sony DSR-500 DV Cam Camcorder and a Canon XL-1 Camcorder. Digital editing was completed on an Apple G4 running OS X with Avid Express Meridian Non-Linear Editing Software version 4.5 with 3D effects, Apple Final Cut Pro 3.0, Adobe After Effects 5.5, and PhotoShop 7.0. Stills were taken with a Sony Mavica and Nikon CoolPix digital cameras.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.950
Threshold uncertainty score0.405

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.044
GPT teacher head0.272
Teacher spread0.228 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2004
Admission routes1
Has abstractyes

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