Guest Editorial: Gender in Aquaculture and Fisheries –Navigating Change
Bibliographic record
Abstract
1 This article was first published as a Guest Editorial in a special issue of the journal Asian Fisheries Science [Gopal N., Williams M.J., Porter M., Kusakabe K. and Choo P.S. 2014. Guest editorial: Gender in aquaculture and fisheries – Navigating change. Asian Fisheries Science Special Issue 27S:1–14.]. It is reproduced here with their kind authorisation. 2 Central Institute of Fisheries Technology, CIFT Jn., Matsyapuri P.O., Cochin – 682 029, Kerala, India 3 17 Agnew Street, Aspley, Queensland, 4034, Australia 4 Department of Sociology, Memorial University, St. John’s, Canada NL A1C 2Z1 5 Gender and Development Studies, School of Environment, Resources and Development, Asian Institute of Technology, P.O. Box 4, Klong Luang, Pathumthani 12120, Thailand 6 147 Cangkat Delima Satu, Island Glades, 11700 Penang, Malaysia * Corresponding author: nikiajith@gmail.com A Special Issue of Asian Fisheries Science journal has been published, which includes 20 papers and a report based on the presentations and posters of the 4th Global Symposium on Gender in Aquaculture and Fisheries (GAF4) held during the 10th Asian Fisheries and Aquaculture Forum, May 2013. GAF4 was the sixth women/gender Symposium organised by the Asian Fisheries Society. For each event, the proceedings or selected papers have been published (Williams et al. 2001; Williams et al. 2002; Choo et al. 2006; Development 2008; Williams et al. 2012a). Worldwide, this is the longest continuous series documenting women and gender issues by a professional fisheries society.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".