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Record W3173213086 · doi:10.1108/rmj-12-2020-0041

Sometimes, green is the outcome: climate action in records management and archives in Canada

2021· article· en· W3173213086 on OpenAlexaffabout
Lois M. Evans

Bibliographic record

VenueRecords Management Journal · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicConservation Techniques and Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSustainabilityCitizen journalismGovernment (linguistics)Public relationsBusinessTerminologyAction (physics)Environmental resource managementKnowledge managementPolitical scienceComputer scienceEconomics

Abstract

fetched live from OpenAlex

Purpose The paper aims to respond to three questions: Are Canadian organizations committed to sustainability? Are there any links between sustainability and records management and archives programs? And, to what extent are records managers, archivists and technologists engaged in climate action? The paper also provides background on climate change in the Canadian and global contexts, defines relevant terminology, and presents a literature review that positions sustainability, adaptation and mitigation in relation to records management and archives. Design/methodology/approach The paper is based on qualitative participatory research involving expert interviews in 24 government agencies, universities and businesses located in 10 Canadian cities. Findings The organizations in the study are committed to sustainability and have developed significant programs and activities in support of this aim. Although the records managers, archivists and technologists interviewed are involved in related activities, there is a gap between what they are doing as a matter of course and the wider sustainability efforts of their parent organizations. As resources are tight, sustainability measurement entails more work and there are no real incentives to add sustainability components to programs, the participants are focused on delivering the programs they are hired to do. As a result, there is a sense of serendipity around outcomes that do occur – “sometimes, green is the outcome”. Research limitations/implications This paper presents the results of research conducted at 24 organizations in 10 Canadian cities, a small but meaningful sample that provides a springboard for considering climate action in records and archives. Based on the discussion, there is a need for a records and archives agenda that directly responds the United Nation's climate action targets: strengthening resilience and adaptive capacity to climate-related hazards and natural disasters; integrating climate change measures into policies, strategies and planning; and improving education, awareness-raising and human institutional capacity on climate change mitigation, adaptation, impact reduction and early warning. In support of this aim, the paper charts possible material topics from the literature and compares these with research findings. Practical implications From a top-down perspective, organizations need to expand sustainability programs to address all business areas, including records and archives. From a bottom-up perspective, records managers and archivists should include adaptation in disaster planning and consider the program benefits of developing economic, environmental and social sustainability initiatives to mitigate climate change. Originality/value The paper defines resilience, sustainability, adaption and mitigation and positions these terms in records management and archives. The paper examines how records managers, archivists and technologists think about sustainability; where sustainability intersects with records and archives work; and how records managers and archivists can engage in climate action.

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)0.008
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.176
Threshold uncertainty score0.956

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.007
Science and technology studies0.0340.015
Scholarly communication0.0110.004
Open science0.0030.007
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0070.000

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.

Opus teacher head0.046
GPT teacher head0.258
Teacher spread0.213 · 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 designQualitative
Domainnot available
GenreEmpirical

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

Citations4
Published2021
Admission routes2
Has abstractyes

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