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Record W2793831543 · doi:10.1139/facets-2017-0083

Quantifying the contribution of zoos and aquariums to peer-reviewed scientific research

2018· article· en· W2793831543 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueFACETS · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsProductivityStaffingAccreditationCredibilityPolitical scienceBiodiversityPeer reviewLibrary scienceBusinessPublic relationsEcologyBiologyComputer scienceEconomicsEconomic growth

Abstract

fetched live from OpenAlex

Modern zoos and aquariums aspire to contribute significantly to biodiversity conservation and research. For example, conservation research is a key accreditation criterion of the Association of Zoos and Aquariums (AZA). However, no studies to date have quantified this contribution. We assessed the research productivity of 228 AZA members using scientific publications indexed in the ISI Web of Science (WoS) database between 1993 and 2013 (inclusive). AZA members published 5175 peer-reviewed manuscripts over this period, with publication output increasing over time. Most publications were in the zoology and veterinary science subject areas, and articles classified as “biodiversity conservation” by WoS averaged 7% of total publications annually. From regression analyses, AZA organizations with larger financial assets generally published more, but research-affiliated mission statements were also associated with increased publication output. A strong publication record indicates expertise and expands scientific knowledge, enhancing organizational credibility. Institutions aspiring for higher research productivity likely require a dedicated research focus and adequate institutional support through research funding and staffing. We recommend future work build on our results by exploring links between zoo and aquarium research productivity and conservation outcomes or uptake.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.381
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.089
GPT teacher head0.367
Teacher spread0.278 · 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