Earth Science Education 5. Effective Industry Outreach. Two Leading Examples from the Mineral Industry
Bibliographic record
Abstract
In an effort to provide information to the public through educators, resource-based industries have commonly produced glossy literature and graphics packages that were not necessarily appropriate for the school curriculum, and therefore remained under used. A major change in approach, that of engaging teachers to design and develop the outreach resources, was successfully implemented by the Mining Association of British Columbia in 1991. Following on this success the Prospectors and Developers Association of Canada developed a similar program in 1994. Since their inception these programs have collectively distributed their resources to more than 10,000 teachers, who have in turn used them in teaching hundreds of thousands of students. It is hoped that this review of these programs will encourage other industry groups to develop similar approaches to outreach resource material. Resume Suite a la mise en commun d'efforts de vulgarisation par l'entremise d'educateurs, des societes du secteur des ressources naturelles ont produit une documentation de haute qualite, mais pas forcement adaptee aux programmes scolaires et qui, en consequence, est demeuree sous utilisee. Par un changement radical d'approche reussi, la Mining Association of British Columbia (association miniere de Colombie-Britannique) a recrute, en 1991, des enseignants qui ont eu mandatde concevoir et de mettre au point unestrategie et des outils de communication appropries. Suivant leurs traces, la Prospectors and Developers Association of Canada (l'association des prospecteurs et des promoteurs miniers du Canada) a mis au point un programme similaire en 1994. Depuis leur creation, ces programmes ont permis de rejoindre plus de 10 000 enseignants, lesquels, a leur tour, ont pu toucher plusieurs centaines d'etudiants. Nous esperons que cette retrospective des programmes de vulgarisation existants incitera d'autres groupes de l'industrie a concevoir et a lancer d'autres programmes de vulgarisation au service de l'industrie des ressources naturelles.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.033 | 0.007 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".