Live projects: a mixed-methods exploration of existing scholarship
Bibliographic record
Abstract
Purpose This paper aims to investigate trends and themes within the literature pertaining to live projects, and in so doing, highlight possible areas of future exploration and research. Design/methodology/approach This paper utilises a Systematic Quantitative Literature Review (SQLR) method, wherein keywords and phrases are entered into selected citation databases generating a reproducible list of literature. This is then refined using a specified list of criteria and read for relevance. The resulting literature forms the basis of qualitative and quantitative analyses and review. Findings The reviewed scholarship demonstrates a surge in publications since the early 2000s, with 75% of publications originating from the USA, Canada, or the UK Furthermore, themes related to live project definitions, outputs and rationales were examined, demonstrating that common factors such as “community”, “construction” and “pedagogy” are not mutually exclusive but tend to overlap, making the topic hard to define. These results also demonstrate a proclivity for projects with a built output. Barriers to live projects were also assessed, and it was found that administrative hurdles, such as time and budget constraints, were the biggest concern to live project practitioners. Finally, critical voices were examined and showed that live projects need to reflect on the nature of their engagement with the community. Research limitations/implications This method, while capturing a substantial portion of the published scholarship, does not capture all live project literature due to limitations such as language and a strong focus on peer-reviewed publications. Furthermore, this research only captures literature that has been published. It does not reflect the variety and extent of live project activity occurring globally. For reasons such as unfamiliarity and inconsistencies with the use of live project terminologies, doubtless many unpublished live projects are conducted–yet not represented in these findings. This study may help live project execution by providing valuable examples of existing trends. Originality/value This paper captures the metadata from 110 live project publications, allowing for wide-ranging analysis, categorisation and discussion on the topic.
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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".