A service‐learning initiative within a community‐based small business
Bibliographic record
Abstract
Purpose The purpose of this paper is to extend previous scholarly writing on community service‐learning (SL) initiatives by looking beyond their use in the not‐for‐profit sector to their potential use in community‐based small businesses. Design/methodology/approach A rationale for the appropriateness of using SL projects in small businesses is provided, and distinctions drawn between small business SL projects and student internships. A case study involving a strategic management project in a community‐based small business is presented. Findings The findings support the usefulness of SL initiatives in small businesses. Benefits to the students include an enhanced understanding of course material, improved learning through the transparent information sharing and experience of the small business owner, increased confidence in strategic management skills, and greater appreciation of community, environmental, and ethical concerns. Benefits to the small business owner included receipt of customized, onsite services that circumvented opportunity, and financial costs associated with other consultation or training options, an unbiased and well‐rounded strategic audit, and receipt of an alternate perspective on the business that would not otherwise be available. Research limitations/implications Future research should explore the use of SL projects in a broader range of undergraduate business courses and continue to develop pragmatic frameworks for initiatives involving small businesses. Factors associated with small business engagement in SL and outcomes for business owners should also be investigated. Practical implications Practical information on the implementation SL initiatives in community‐based small businesses is provided, along with guidance on dealing with potential risk management concerns related to non‐conflict of interest, confidentiality, and liability. Originality/value Previous approaches to SL have focused almost exclusively on partnerships with not‐for‐profit agencies. This paper supports the usefulness of SL initiatives in for‐profit, community‐based small businesses.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.017 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.003 |
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".