Climate Crisis, Libraries, and Evidence-Based Decision Making
Bibliographic record
Abstract
Introduction: In October 2018, the United Nations Intergovernmental Panel on Climate Change stated that 'transformative change' is needed to limit catastrophic impacts of global heating. In 2019, the UN's Emissions Gap Report described their findings as 'bleak' as emissions continued to rise, increasing risks to ecosystems, communities, and health. The level of change necessary is stark and involves steep reductions in emissions, especially in high emitting countries like Canada. One of the most significant contributors is air travel. Methods: This study applies climate science evidence to library professional activities by analyzing the emissions produced by air travel to past CHLA conferences. It uses conference attendance data from CHLA's three most recent conferences. Emissions calculations assume attendees used air travel for trips of more than 500km, or for the 2018 conference, travel from outside of Newfoundland. Results: As in similar studies, emissions resulting from air travel to CHLA conferences comprise a substantial portion of a sustainable per capita annual carbon budget. Significantly reducing air travel is necessary to meet climate targets. Discussion: This assessment addresses only one part of the carbon footprint of the three CHLA conferences studied and offers no baseline for other emissions sources, such as food and accommodations, that could be used in future measurements and decarbonization efforts. However, air travel is the most significant source of emissions from professional development activities. Thus, this poster also explores low carbon meeting options, professional roles in advocating for policy change, and implications for COVID-19 recovery efforts.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.006 | 0.000 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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 teacher head, 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".