Adversity Creates Serendipity: COVID-19 Lockdown Experiences of Six Young Women in Hospitality and Tourism
Bibliographic record
Abstract
Under the umbrella of a critical feminist theoretical framework, this exploratory paper unpacks how six young women, residing in New Zealand, Canada and the UK, within the hospitality and tourism industry, discursively managed their COVID-19 lockdown and related experiences, amidst the social-psychological dilemma of being available and/or wanting to work, yet not being able to work. This study adds to a current gap in critical feminist tourism research by deploying six young women’s emotional experience of vulnerability as hospitality and tourism workers during a global crisis to generate nuanced understandings about how they used this vulnerable experience to gain empowerment and transformation. Data was collected via interviews between April and May 2021, and a discourse analysis was carried out on the interview transcripts underpinned by a social constructionist framework. The finding of an “adversity creates serendipity” repertoire and its resources of “luck,” “having the time,” and “appreciating things” offer ways of managing the challenges posed during the lockdown. Interwoven through an adversity creates serendipity repertoire was a social connectedness theme, which is examined in relation to the indigenous Māori concept of whanaungatanga. The findings are relevant because they demonstrate effective strategies for managing the adverse psycho-social affects of the COVID-19 lockdowns. The findings have application for a range of occupational sectors within society, where working remotely is not possible during a national pandemic lockdown or during other events leading to similar workplace limitations.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.013 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".