The postulate for the systematic mainstreaming of impairments in Tourism Education in South Africa: A literature synthesis.
Bibliographic record
Abstract
This article seeks to ascertain the existence of a void in mainstreaming impairment issues and mildphysically impaired persons in tourism education. The insights were obtained from Afro-centric tourism studies on tourists with disabilities needs, motivations, expectations and wants (Breedt, 2007; Chikuta, 2015; Chikuta et al., 2017, 2018; Snyman 2002). Hence, the paper identifies the problem, ascertaining the extent of the gaps, and then making propositions to the tourism education. An extensive literature review was conducted through triangulating Tesch and Creswell’s steps in qualitative data analysis. North-West University (Boloka) Institutional Repository, Scopus, Google Scholar, JSTOR, Emerald Insights Journals, Science Direct, SAePublications, Sabinet, Union Catalogue of Theses and Dissertations (1919-2001), NEXUS, National Electronic Thesis and Dissertations Portal, DART, Caltech Thesis and Theses Canada were the sources of texts. 10 000 articles were accessed and only 150 texts that dated from 1990-2018 (except for seminal theory) were set for this paper. The search scoped the usage of terms impairments, disability and tourism education as contextualised to policy and practice. The findings noted a void in mainstreaming impairments issues, and/or mild-physically impaired persons within the tourism education. This is prevalent in the global tourism village, hence a cause for tourism human resources’ lack of capacity/aptitude to serve visitors with impairments. However, the current emphasis is on physical accessibility, though skewed towards the mobile impairments at the expense of other types of impairments. The problem comes in ‘how can tourism/hospitality personnel behave and/ or which attitude should they exhibit while serving a visitor with impairment’. Such a dilemma may arise due to a lack of knowledge and interactive exposure among non-impaired tourism/hospitality personnel. To this effect, unsatisfactory service delivery is not an exception. The paper’s propositions scoped the mainstreaming of impairments and mild-physically impaired persons in tourism education. Such would emanate from inter alia, the tourism education policy, tourism curricula, curricula content and the delivery/teaching and learning environs. Such aspects once considered effectively would bring capacity/aptitude in tourism human resources (either with or without impairments) to serve visitors with impairments in the pre-arrival period, and also during and post-tourism/hospitality service consumption process.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 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".