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Record W2027635175 · doi:10.1017/s1743921311003607

Maximum outreach. . . minimum budget

2009· article· en· W2027635175 on OpenAlexaboutno aff
Mary Beth Laychak

Bibliographic record

VenueProceedings of the International Astronomical Union · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicDiverse Educational Innovations Studies
Canadian institutionsnot available
Fundersnot available
KeywordsOutreachExhibitionPresentation (obstetrics)Public relationsMedical educationPolitical scienceGeographyMedicineArchaeologyLaw

Abstract

fetched live from OpenAlex

Abstract Many astronomical institutions have budgetary constraints that prevent them from spending large amounts on public outreach. This is especially true for smaller organizations, such as the Canada-France-Hawaii Telescope (CFHT), where manpower and funding are at a premium. To maximize our impact, we employ unconventional and affordable outreach techniques that underscore our commitment to astronomy education and our local community. We participate in many unique community interactions, ranging from rodeo calf-dressing tournaments to art gallery exhibitions of CFHT images. Further, we have developed many creative methods to communicate complex astronomical concepts to both children and adults, including the use of a modified webcam to teach infrared astronomy and the production of online newsletter for parents, children, and educators. This presentation will discuss the outreach methods CFHT has found most effective in our local schools and our rural community.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.184
Threshold uncertainty score0.616

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0070.005
Open science0.0020.006
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.1840.036

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 head0.014
GPT teacher head0.217
Teacher spread0.202 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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
Published2009
Admission routes1
Has abstractyes

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Same venueProceedings of the International Astronomical UnionSame topicDiverse Educational Innovations StudiesFrench-language works237,207