Kenyan Exports of Nile Perch: The Impact of Food Safety Standards on an Export-Oriented Supply Chain
Bibliographic record
Abstract
Over the past decade, exports of fish and fisher\ny products from developing countries have increased\nrapidly. However, one of the major challenges fa\ncing developing countries in seeking to maintain and\nexpand their share of global markets is stricter f\nood safety requirements in industrialized countries.\nKenyan exports of Nile perch to the European Union\nprovide a notable example of efforts to comply with\nsuch requirements, overlaid with the necessity to ov\nercome restrictions on trade relating to immediate\nfood safety concerns. Although food safety requirement\ns were evolving in their major markets, most\nnotably the European Union, most Kenyan exporte\nrs had made little attempts to upgrade their hygiene\nstandards. Likewise, the legislative framework of\nfood safety controls and facilities at landing sites\nremained largely unchanged. Both exporters and th\ne Kenyan government were forced to take action\nwhen a series of restrictions were\napplied to exports by the European Union over the period 1997 to 2000.\nProcessors responded by upgrading their hygiene c\nontrols, although a number of facilities closed,\nreflecting significant costs of compliance within the c\nontext of excess capacity in the sector. Remaining\nfacilities upgraded their hygiene controls and made e\nfforts to diversify their export base away from the\nEuropean. Legislation and control mechanisms we\nre also enhanced. Hygiene facilities at landing\nbeaches were improved, but remain the major area of weakness.\nThe Kenyan case illustrates the\nsignificant impact that stricter food safety requirements\ncan have on export-oriented supply chains. It also\ndemonstrates how such requirements can exacerbate existing pressures for restructuring and reform, while\nprevailing supply and capacity issues constrain the manner\nin which the supply chain is able to respond.\nIn Kenya most of the concerted effort to comply\nwith these requirements was stimulated by the sudden\nloss of market access in very much a ‘crisis manage\nment’ mode of operation,\nillustrating the importance\nof responding to emerging food safety requireme\nnts in a proactive and effective manner.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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.
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 source (direct Gemma or distilled Codex), 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".