Experiences of intense work for individuals working in the information technology (IT) sector and its impact on their lives
Bibliographic record
Abstract
This dissertation, embedded in the Workforce Ageing in the New Economy (WANE) project funded by the Social Sciences and Humanities Research Council of Canada, explores intense work for individuals working in the Australian information technology (IT) sector. It builds on the existing literature using a qualitative lens to yield an alternative perspective to the phenomenon of work intensity. Using a life course perspective to understand the complexity and tensions that individuals experience in combining work with their personal lives, this study explores the various manifestations and the impact of intense work for individuals. Further, the relationship between ageing and intense work for individuals is examined. The study, which is based on constructivist inquiry, presents the findings from the perspective of the individual using seven case studies. Individuals were employed in two organisations based in a major city of Australia, and one male and female were selected for study in each of three different age groups. The seventh case was a male aged over sixty. Although each individual's experience of intense work is unique, a number of commonalities are evident. These constitute the main findings of this dissertation and pertain to the IT labour market, the workplace and the individual's work/life interaction. This dissertation develops a conceptualisation of the intense work experience. Comprised of two levels, the meta-level consists of the life course guiding principles that underpin the individual's life events and transitions. The base-level of the conceptualisation has three main components: the intense work structure, the non-work structure and the interaction between the structures. All three components are in states of flux enabling each of them to change as the context changes. An individual's experience of intense work can fluctuate and activities within an individual's non-work life or domain vary from time to time. As a consequence, the impact of intense work on individual's lives, and vice-versa, will change. This conceptualisation recognises diverse intense work experiences between individuals but also for individuals, as their experiences change over time. When brought together, the meta-level provides a lens for viewing how the life course of individuals underpins the experience of intense work in the context of the work/life interaction (the base-level). Findings from the study have implications at a number of levels and recommendations pertain to organisational policy and a practice-based level, as well as at the level of the individual.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".