Impact of Management Practices in Industries in the Industrial – Free – Trade Zones in Douala, Littoral Region of Cameroon: “Challenges and Prospects”
Bibliographic record
Abstract
In Cameroon of late, there is growing consciencious that the deleterious impacts of industrial activities on safety health and environmental quality has motivated government and industries to adopt environmental management practices such as the EMSs and EMA, that is, Environmental Management Systems, and Environmental Management Accounting respectively at the least. This paper however, examines the implementation of EMSs and EMA amongst others in industries in the Industrial –Free – Trade Zones of the South West and Littoral Regions of Cameroon that interact with its environment which has been affected by the effluents emanating from industrial activities.This paper also presents an overview of various initiatives like policies that have been crafted by the government of Cameroon to address the problems of industrial activity such as pollution etc. It also seeks to prescrible recommendations which could be used to save the regions, from industrial pollution. After the participation of Cameroon in the Earth’s Summit in Rio de Janerio, Brazil (1992), and ever since the publication of the Brunditland Commission’s Landmark Report ‘‘Our Common Future’’, in (1987), the government has taken significant steps to overhaul its institutional framework vis – à – vis the regulation of industrial pollution.Through a questionnaire based survey carried but from January to July 2016 with the sampled industries in the Industrial – Free – Trade – Zones of the South West and Littoral Regions of Cameroon, data was collected. This paper also aims at addressing motivational factors, implementation hurdles as well as benefits accrued by these industries as a result of adapting environmental management systems in their management practices generally. Studies also support that many benefits arise as a result of EMSs and EMA enforcement, but the paradox is the plethora of hurdles that still persist in industries. Against this background, this paper concludes by prescribing recommendations that seek to promote management practices such as EMSs and EMA in industries in Industrial – Free – Trade – Zones in Cameroon.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".