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Record W2938980627 · doi:10.1139/cjfr-2018-0402

“From nude calendars to tractor calendars”: the perspectives of female executives on gender aspects in the North American and Nordic forest industries

2019· article· en· W2938980627 on OpenAlexvenueno aff
Pipiet Larasatie, Gintare Baublyte, Kendall Conroy, Eric Hansen, Anne Toppinen

Bibliographic record

VenueCanadian Journal of Forest Research · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicGender Diversity and Inequality
Canadian institutionsnot available
FundersU.S. Forest ServiceLembaga Pengelola Dana PendidikanOregon State University
KeywordsDiversity (politics)Gender diversityCultural diversityForest industryForest managementPolitical scienceDemographic economicsGeographyManagementForestryEconomics

Abstract

fetched live from OpenAlex

Increasing gender diversity is no longer just the right thing to do, but also the smart thing to do. Although there is general literature about gender diversity and the perspectives of females in top management and leadership, there are, however, very few forest sector specific studies. This exploratory study utilizes interviews to better understand how female executives in North America and the Nordic countries of Finland and Sweden perceive the impact of the situation of gender diversity in the forest industry. Respondents also provide career advice for young females entering or considering entry into the industry. Female executives in both regions agree that although the forest sector is still seen as a male-oriented industry, there are signs of increasingly positive attitudes regarding industry and company culture towards the benefits of greater gender diversity; however, the described changes represent an evolution, not revolution. Interestingly, despite the status of Nordic countries as leaders in bridging the gender gap, respondents from this region believe that there is significant progress yet to be made in the forest industry, especially at the entry level. With respect to career development, North American respondents suggested that young females should consider sacrificing their social life and leisure time activities, whereas Nordic respondents instead emphasized personal supports or using exit strategy from an unsupportive company or boss.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.611
Threshold uncertainty score0.710

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.148
GPT teacher head0.361
Teacher spread0.212 · 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 designObservational
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

Citations22
Published2019
Admission routes1
Has abstractyes

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