Orienting the Sustainable Management of Chemicals and Waste toward Indigenous Knowledge
Bibliographic record
Abstract
ADVERTISEMENT RETURN TO ISSUEViewpointNEXTOrienting the Sustainable Management of Chemicals and Waste toward Indigenous KnowledgeJames M. Ataria*James M. AtariaCawthron Institute, Nelson 7010, Aotearoa, New Zealand*[email protected]More by James M. AtariaView Biography, Michelle MurphyMichelle MurphyTechnoscience Research Unit, University of Toronto, Toronto, Ontario M5S 1C6, CanadaMore by Michelle Murphy, Deborah McGregorDeborah McGregorOsgoode Hall Law School, York University, York, Ontario M3J 1P3, CanadaMore by Deborah McGregor, Susan ChiblowSusan ChiblowSchool of Environmental Sciences, University of Guelph, Guelph, Ontario N1G 2W1, CanadaMore by Susan Chiblow, Bradley J. MoggridgeBradley J. MoggridgeCentre for Applied Water Science, University of Canberra, Canberra, ACT 2617, AustraliaMore by Bradley J. Moggridge, Daniel C. H. HikuroaDaniel C. H. HikuroaTe Ao Ma̅rama - Centre for Fundamental Inquiry, Ma̅ori Studies, Te Wa̅nanga o Waipapa, in the Faculty of Arts, University of Auckland, Auckland 1010, Aotearoa, New ZealandMore by Daniel C. H. Hikuroa, Louis A. Tremblay*Louis A. TremblayCawthron Institute, Nelson 7010, Aotearoa, New ZealandSchool of Biological Sciences, University of Auckland, Auckland 1142, Aotearoa, New Zealand*[email protected]More by Louis A. Tremblayhttps://orcid.org/0000-0002-3586-3995, Gunilla ÖbergGunilla ÖbergThe University of British Columbia, Vancouver, British Columbia V6T 1Z4, CanadaMore by Gunilla Öberg, Virginia BakerVirginia BakerInstitute of Environmental Science and Research Limited (ESR), Wellington 5022, Aotearoa, New ZealandMore by Virginia Baker, and Bryan W. Brooks*Bryan W. BrooksDepartment of Environmental Science, Baylor University, Waco, Texas 76798, United States*[email protected]More by Bryan W. Brookshttps://orcid.org/0000-0002-6277-9852Cite this: Environ. Sci. Technol. 2023, 57, 30, 10901–10903Publication Date (Web):July 17, 2023Publication History Received14 June 2023Published online17 July 2023Published inissue 1 August 2023https://pubs.acs.org/doi/10.1021/acs.est.3c04600https://doi.org/10.1021/acs.est.3c04600article-commentaryACS PublicationsCopyright © 2023 American Chemical Society. This publication is available under these Terms of Use. Request reuse permissions This publication is free to access through this site. Learn MoreArticle Views1860Altmetric-Citations-LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail PDF (2 MB) Get e-AlertscloseSUBJECTS:Environmental pollution,Plastics,Sustainability,Waste management,Wastes Get e-Alerts
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 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 | 0.001 | 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 | 0.004 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.055 | 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".