PROMOTING ENVIRONMENTALLY SUSTAINABLE BUSINESS IDEAS AMONG TERTIARY STUDENTS: THE CASE OF COURSES AT DAR ES SALAAM TUMAINI UNIVERSITY
Bibliographic record
Abstract
Dar es Salaam Tumaini University (DarTU), formerly known as Tumaini University, Dar es Salaam College (TUDARCo), in its strategic plan 2020/21 – 2024/25 focuses on innovation and entrepreneurship in the growth of developing nations like Tanzania, especially in creating an informed and responsible citizen by preparing students for personally rewarding and socially helpful jobs. This focus is rooted in its understanding on how entrepreneurship and innovation are crucial forces behind economic expansion. In achieving this, DarTU, through the School of Business Studies (SoBS), Department of Marketing and Entrepreneurship, established two courses; MGMT 225 Innovation, Entrepreneurship and Enterprise Development; and MGMT 311 Harnessing Entrepreneurship and an Innovators Mindset. These two modules are taught to students in all Schools at the University. One of the focus of this course is to enable students to come up with business proposals that promote environmentally-friendly business, to address the sustainable development goal (SDG) 8; Promote sustained, inclusive and sustainable economic growth, full and productive employment and decent work for all. Special focus was on target 8.1 Sustainable economic growth, and target 8.6 Promote youth employment, education and training. This paper presents the top five businesses that adequately focused on environmentally-friendly business. The paper employs a descriptive research design, and selects the top five, out of 205 business model canvases which focused on environmental sustainability. Businesses were rated according the Canadian Youth Innovation Fund (YIF) criteria for environmental inclusion in a business model canvas. A discussion follows the presentation, where it shows that these businesses, among other things, innovative ways of cleaning plastic waste, restore health to water ecosystem, create businesses that add value to waste and re-use paper instead of throwing it away after use. The study recommends other higher learning institutions to adapt the methods of teaching and including environmental aspects in teaching innovation and entrepreneurship courses to their students.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.015 | 0.004 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".