A case of Intention Deficit Disorder? ICT policy, disadvantaged schools, and leaders
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Since the mid-1990s, government policies in the USA, Canada, England, and Australia have promoted the need to produce an ICT skilled workforce in order to ensure national competitiveness in globalised economic conditions. In this article, we examine the ways in which these policy intentions in 1 state in Australia were translated into a techno-determinist and technocentric plan which focused primarily on getting wired up and connected. We summarise the findings from 2 projects: an investigation of a state-wide principals' professional development programme and an action research study investigating literacy, educational disadvantage, and information technologies. We found significant differences in the distribution of the physical and human capabilities between schools which made the task of engaging with ICT harder for some than others. Nevertheless, we suggest that some school leaders did develop innovative practice. We suggest that policy deficits made it difficult for school leaders to grapple with the dimensions of and debates about the kinds of educational changes that schools and school systems should be making. © 2006 Taylor & Francis.
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.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 it