Consolidated Framework for Implementation Research

Nice resource website for CFIR - Connected to TCI somehow

Shared by Jimmy Breeze, like and 5 saves total

Anthropeum

Museum game where you guess an artifact's time and place.

Shared by Bryan Alexander, like and 2 saves total

‘Can a machine do this job?’ is the wrong question

https://www.linkedin.com/feed/update/urn:li:activity:7472305181192536064/?utm_source=share&utm_medium=member_desktop&rcm=ACoAAAJrHvsBTNSt86Fs5GFHTEcIGOuwz83Dslg

1) Capitalism's great achievement was moving activity out of the household and into the market — turning domestic production into paid specialisation, creating jobs, and making output visible to the national accounts. AI-enabled self-service might quietly reverse that centuries-long trend.

2) When a technology automates tasks within a service, it can trigger a Jevons paradox: the service gets cheaper, demand expands, and employment grows. That is what ATMs did, and why automation has so rarely produced mass unemployment. But the paradox holds only when the technology makes the existing service model more efficient. When it lets people do the work themselves, demand for the service collapses.

3) AI extends this even to the manual trades, the supposed safe haven of the AI age. If a homeowner can ask a chatbot why their boiler keeps losing pressure, heating engineers lose call-outs.

4) When work shifts to the consumer, it vanishes from the economy statisticians measure. Replace a billing department with a chatbot and a firm records lower costs and higher output per worker; the national accounts register a productivity gain. But the hours patients spend decoding their own test results appear nowhere — not in labour statistics, not in GDP. As self-service spreads into professional domains, that blind spot will grow.

Shared by Jimmy Breeze, like and 1 save total

Arvind Naryan on AI for work

There’s a big, under-appreciated reason why people may have very different experiences and opinions about using AI for work — are they using it for tasks they’re already an expert at, or tasks they can’t do themselves? The former leads to a *growth cycle* and the latter leads to a *dependence spiral*.

Shared by Jimmy Breeze, like and 1 save total

The Mystery of the Vanishing Benefits: An Introduction to Impact Evaluation - Martin Ravallion

***The OG***

Featuring my research hero Ms. Sensible Sociologist

Is MSS Michael Woolcock?!

---

A Chance Encounter with Ms. Sensible Sociologist

The day before she is due to present her results to her boss, Ms. Analyst acciden-
tally bumps into her old friend Ms. Sensible Sociologist, who now works for one
of Labas’s largest nongovernmental organizations, the Social Capital for Em-
powerment Foundation (scef). Ms. Analyst tells Ms. Sociologist all the details
about what she has been doing on proscol.

Ms. Sociologist’s eyes start to roll when Ms. Analyst talks about “unbiased
estimates” and “propensity scores.” “I am no expert on that stuff, Speedy. But
I do know a few things about proscol. I have visited some of the schools in
northwest Labas where there are a lot of proscol children, and I meet proscol
families all the time in my work for scef. I can tell you they are not all poor, but
most are. proscol helps.
“However, this story about ‘forgone income’ that Tangential came up with, I
am not so sure about that. Economists have strange ideas sometimes. I have seen
plenty of children from poor families who work as well as go to school. Some of
the younger ones who are not at school don’t seem to be working. Maybe Tan-
gential is right in theory, but I don’t know how important it is in reality.”
“You may be right, Sense. What I need to do is check whether there is any
difference in the amount of child labor done by proscol children versus a
matched comparison group,” says Ms. Analyst. “The trouble is that the lss did
not ask about child labor. That is in another lbs survey. I think what I will do is
present the results with and without the deduction for forgone income.”
“That might be wise,” says Ms. Sociologist. “Another thing I have noticed,
Speedy, is that for a poor family to get on proscol, it matters a lot which school
board area (sba) the family lives in. All sbas get a proscol allocation from the
center, even sbas that have very few poor families. If you are poor but living in
a well-to-do sba, you are more likely to get help from proscol than if you live
in a poor sba. The authorities like to let all areas participate for political rea-
sons. As a result, it is relative poverty—relative to others in the area where you
live—that matters much more than your absolute level of living.”
“No, I did not know that,” replies Ms. Analyst, a little embarrassed that she
had not thought of talking to Ms. Sociologist earlier, since this could be impor-
tant.
“That gives me an idea, Sense. I know which school board area each house-
hold belongs to in the lbs survey, and I know how much the center has allo-
cated to each sba. Given what you have told me, that allocation would influ-
ence participation in proscol, but one would not expect it to matter for school
attendance, which would depend more on one’s absolute level of living, family
circumstances, and I guess characteristics of the school. So the proscol budget
allocation across sbas can be used as instrumental variables to remove the bias
in my estimates of program impact. ”
Ms. Sociologist’s eyes roll again, as Ms. Analyst says farewell and races back
to her office. She first looks into the original file she was given, to see what rules
are used by the center in allocating proscol funds across sbas. A memo from
the ministry indicates that allocations are based on the number of school-age
children, with an “adjustment factor” for how poor the sba is thought to be.
However, the rule is somewhat vague.

Shared by Jimmy Breeze, like and 1 save total

Conversations at Scale: Robust AI-led Interviews

Interesting approach

---

The advent of large language models (LLMs) creates new opportunities to conduct qualitative in-
terviews at scale and at low cost, with thousands of respondents, thereby bridging qualitative and
quantitative methods. We develop a simple, versatile approach for researchers to run AI-led qualitative
interviews, including voice interviews. We assess its robustness by drawing comparisons to human ex-
perts and with several respondents-based quality metrics. The versatility of the approach is illustrated
through four broad classes of applications: eliciting key factors in decision making, political views, sub-
jective mental states, and mental models of the effects of public policies. High performance ratings are
obtained in all of these domains. Our applications highlight the potential of AI-led interviews as a tool
for measurement, hypothesis generation, and discovering mechanisms.

--

Related resources -> https://colab.research.google.com/drive/1sYl2BMiZACrOMlyASuT-bghCwS5FxHSZ

Shared by Jimmy Breeze, like and 1 save total

Explain THIS: Implementation Science - THIS Institute - The Healthcare Improvement Studies Institute

Typically good intro / primer on IS from THIS
Based on the Kislov and Wilson resource -> https://www.cambridge.org/core/elements/implementation-science/9E9361E2F6C1A3B894C6D202031ECD19

Shared by Jimmy Breeze, like and 1 save total

Implementation Science by Roman Kislov & Paul Wilson - Series: Elements of Improving Quality and Safety in Healthcare

Excellent intro / primer to IS

Shared by Jimmy Breeze, like and 1 save total

The Consolidated Framework for Implementation Research (CFIR) User Guide: a five-step guide for conducting implementation research using the framework | Implementation Science | Springer Nature Link

Fantastic resource for CFIR
Worth reading closely
Feels like Zack v Allen's AI Directed Content Analysis will have used / drawn heavily on this

Shared by Jimmy Breeze, like and 2 saves total

Integrating qualitative research within a clinical trials unit: developing strategies and understanding their implementation in contexts | Trials | Springer Nature Link

Shared by Jimmy Breeze, like and 1 save total