Bibliographic record
Abstract
1. Recent Development in New Ways of Organizing Work. Clare Kelliher and Julia Richardson 2. Paradoxical Consequences of the Use of Blackberrys? An Application of the Job Demand-Control-Support Model. Charles-Henri Besseyre des Horts, Kristine Dery and Judith MacCormick 3. Temporary Work and Temporary Work Agencies in Australia: Going From Bad to Worse? Angela Knox 4. Women Doing Their Own Thing: Our Picture of Modern Women at Work? Doris Ruth Eikhof and Juliette Summers 5. Flexible Work, Flexible Selves?: The Impact of Changing Work Practices on Identity. Carol Linehan 6. New Working Practices: Identity, Agency and the Emotional Experience of Remote Working. Jennifer Wilkinson and Carol Jarvis 7. Flexwork in Canada: Coping with Dis-Ease? Julia Richardson 8. Understanding Processes of Individual Resistance to New Working Practices: The Case of Deciding Not To Embrace Telework. Daniel Wade Clarke 9. Telecommuters: Creative Or Exhausted Workers? A Study into the Conditions under Which Telecommuters Experience Flow and Exhaustion. Pascale Peters and Marijn Wildenbeest 10. Innovation in Distributed Teams: The Duality of Connectivity Norms and Human Agency. Paul Collins and Darl Kolb 11. Challenging New Ways of Working for Remote Managers in Global Collaborative Work Environments. Petra Bosch-Sijtema, Renate Fruchter, Matti Vartiainen and Virpi Ruohomaki 12. Observations and Conclusions on New Ways of Working. Clare Kelliher and Julia Richardson
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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.009 | 0.034 |
| Scholarly communication | 0.024 | 0.022 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.020 | 0.006 |
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".