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Record W4395074287 · doi:10.3389/fevo.2024.1411948

Editorial: Women in conservation and restoration ecology 2022

2024· editorial· en· W4395074287 on OpenAlexafffundabout
Isabel Marques, Diana J. Hamilton, Myriam A. Barbeau, Clare Morrison, Aliénor L. M. Chauvenet

Bibliographic record

VenueFrontiers in Ecology and Evolution · 2024
Typeeditorial
Languageen
FieldEnvironmental Science
TopicForest Management and Policy
Canadian institutionsUniversity of New BrunswickMount Allison University
FundersFundação para a Ciência e a TecnologiaNatural Sciences and Engineering Research Council of Canada
KeywordsEcologyRestoration ecologyConservation biologyGeographyFront (military)Biology

Abstract

fetched live from OpenAlex

Women scientists conduct ground-breaking research across the world. Yet, they made up to only 31.7% of all researchers globally in 2021, according to a recent report from the United Nations Educational, Scientific and Cultural Organization (UNESCO, 2024), and only about 4 % of Nobel Prize laureates for science and medicine were women as of 2023 (The Nobel Prize, 2024). More broadly, the World Economic Forum (2023) reports that while workforce participation (based on LinkedIn profiles) of women and men is approximately equal in non-STEM fields, in STEM fields women represent only about 29% of workers, and the share of women's participation declines as positions become more senior. This is in part due to the "leaky pipeline" phenomenon, in which numbers of women in STEM fields decline progressively from student and early career roles to senior positions (Resmini, 2016). This leaves fewer women available for senior positions and the opportunities and accolades that come at a later career stage. It is also due to deeply entrenched but hidden biases faced by those who remain -which also contribute to the leaky pipeline in a persistent feedback loop. In short, while there are fewer women at senior levels, it is not because they are less competent or less passionate than men. Even accounting for this, women are still experiencing the consequences of unconscious bias throughout their careers. The academic currency for success is publications (preferably in high impact journals), research funding (preferably national and competitive) and esteem (respect and impact in one's field); there is evidence of gender bias in all of these.Women get fewer opportunities for high impact publications. Nature recently published an editorial headlined "Nature publishes too few papers from women researchers -that must change" (Nature, 2024). In it, the authors note that only 17 % of corresponding authors identify as women. They also note geographic differences, with percentages ranging from 4% (Japan) to 22% (United States), and find that acceptance rates among manuscripts sent for review were lower for woman-authored papers (46 %) than for those authored by men (55 %).Women are less likely to apply for competitive national funding (Schmaling and Gallo, 2023). In Canada, for example, according to the most recent funding statistics from the Natural Sciences and Engineering Research Council, only 24% of applicants identify as women, though success rates are similar for women and men (NSERC, 2023). Among early career researchers, women make up 37 % of applicants and 50 statistics are reflected in other countries, such as Australia (Kingsley et 2023), the 51 United States (Rissle et al., 2020), and Kingdom (Head et al., 2013;52 EPSRC, 2022). 53In conservation careers, men influence conservation and science decisions more than 54 women (James et al., 2023) • Global trends in geospatial conservation planning (Cobb et al., 2024). 85While the papers in this collection partly reflect the fields of expertise and backgrounds 86 of the guest editors, we hope that this collection will help foster an international network 87 of women researchers working in conservation and restoration. We aim to provide an 88 impetus for future collaborations and discussions. We also hope that this collection of 89 discoveries helps to support and encourage other women wishing to pursue a career in 90 conservation and restoration ecology. 91The authors declare that the research was conducted in the any 99 commercial or financial relationships that could be construed as a potential conflict of 100 interest.Editors of this Special Issue, we would like to express our deep appreciation 104 to all authors whose valuable work was published under this issue, as well as the time 105and efforts of all reviewers, which altogether, contributed the success of the 106 edition. We are grateful to the many woman scientists with whom we have worked and 107 discussed these important issues. We also thank Julianne M.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Editorial · Consensus signal: Editorial
Teacher disagreement score0.099
Threshold uncertainty score0.784

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.003
GPT teacher head0.210
Teacher spread0.207 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEditorial

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

Citations2
Published2024
Admission routes3
Has abstractyes

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