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Record W4408430572 · doi:10.5194/egusphere-egu25-14200

Promoting Geosciences: Effective Communication Strategies for the International Geological Congress (IGC) 2028 in Calgary, Alberta, Canada.

2025· preprint· en· W4408430572 on OpenAlexaffabout
Katherine Boggs, Amrine Dubois Gafar, David W. Eaton, Lilian Navarro, Jerry Demorcy, Holly Bley, R. J. T. Carlisle

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldComputer Science
TopicSeismology and Earthquake Studies
Canadian institutionsConference Board of CanadaCape Breton UniversityAlberta EnergyUniversity of CalgaryMount Royal University
Fundersnot available
KeywordsLibrary sciencePolitical scienceComputer science

Abstract

fetched live from OpenAlex

The International Geological Congress (IGC) 2028 is returning to Canada, after an absence of over 50 years (1972, Montreal). Hosted in Calgary, Alberta, this will mark the first IGC to be held in western North America. We look forward to showcasing our “Gorgeous Geology” and “Legendary Landscapes” with the world’s geoscience community. Field trip opportunities include the Mohorovic discontinuity and glacial fjords in UNESCO World Heritage Site (UWHS) Gros Morne National Park (Newfoundland), the Carboniferous Forests at UWHS Joggins Fossil Cliffs (Nova Scotia), the Logan Line separating the Appalachians from the Grenville Province of the Canadian Shield in UWHS Quebec City (Quebec), the Cretaceous Dinosaur fossil beds at UWHS Dinosaur Provincial Park (Alberta), and evidence for the Cambrian Explosion of Life in the Burgess Shale surrounded by glaciers across the UWHS Rocky Mountain Parks (Alberta/British Columbia). Potential Indigenous cultural day trips from Calgary include Blackfoot Crossing, UWHS Head-Smashed-In Buffalo Jump, and UWHS Writing-on-Stone Provincial Park, also known as the “Blackfoot Archives” because of the thousands of pictographs throughout the park.Here we report on the overall communications plan, starting with phase one leading into IGC 2024 in which a powerful social media presence became the potential game-changer to connect with the target audiences such as the national and global geoscience community, as well as the general public. This connection built brand awareness while unearthing enthusiasm for the destination and program. Stage one for the social media campaign involved a recent three-month social media campaign with daily bilingual postings on Facebook, Instagram, X, LinkedIn and YouTube. Social media was important for achieving the goals of: i) promoting Canadian geosciences, ii) highlighting the conference tagline “Geosciences for Humanity” and iii) building awareness about the Canadian bid. During IGC 2024 the social media team also promoted the events that happened at the Canadian Booth and Reception, reflecting Calgary’s renowned hospitality such as the White Hat Ceremony swearing in 30 IGC delegates as honorary Calgarians. This strategy united the international geoscience community, emphasizing the collaborative spirit that we aim to foster for IGC 2028.The stage two of the social media (post-bid) campaign started at the end of 2024. Weekly themes promote Indigenous and geotourism offerings across Canada, with three weekly postings to showcase content. After winning the bid to host IGC 2028, interest from the local media was sparked after a press release led by the University of Calgary framing this as the “Olympics of the Geosciences”. Co-chairs Boggs and Eaton were interviewed on TV and Radio. Further press releases will follow in upcoming years to profile plenary speakers and advertise the Keynote Daily Themes (KDT) to local public schools and universities across Canada. KDTs such as “Space and Planetary Geosciences” will springboard off the Artemis II Mission which will be circumnavigating the moon in 2025 with Canadian Astronaut Jeremy Hansen onboard.

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)0.006
metaresearch head score (Gemma)0.006
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: none
Teacher disagreement score0.561
Threshold uncertainty score0.873

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.006
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.004
Science and technology studies0.0090.004
Scholarly communication0.0100.005
Open science0.0020.010
Research integrity0.0070.006
Insufficient payload (model declined to judge)0.1380.034

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 head0.020
GPT teacher head0.273
Teacher spread0.254 · 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
Published2025
Admission routes2
Has abstractyes

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