International Students and the Law

Award-Winning Canadian Immigration and Refugee Law and Commentary Blog

Blog Posts

Coach Will: New Vocabulary Words Tomorrow’s Immigration Practitioners Will Need To Know

As a resource, and to buy time as I am writing more substantive blogs, I wanted to share a #CoachWill blog on new vocabulary, terminology that tomorrow’s immigration practitioners will need to know, learn, advise their clients on, and spend time with. I am still very much learning these terms and their impact, but it gives us a mutual starting point to grow our knowledge of how Canadian immigration law will be impacted moving forward:

 

Advanced Analytics: which is composed of both Predictive and Prescriptive components, consists of using computer technology to analyze past behaviours, with the goal of discovering patterns that enable predictions of future behaviours. With the aid of a team of computer science, data, IT, and program specialists, AA may result in the creation of a model that can perform risk triage and enable automated approvals on a portion of cases, thereby achieving significant productivity gains and reducing processing times. [As defined in IRCC’s China-Advanced Analytics TRV Privacy Impact Assessment]

Artificial Intelligence: Encompassing a broad range of technologies and approaches, Al is essentially the field of computer science dedicated to solving cognitive problems commonly associated with human intelligence, such as learning, problem solving, and pattern recognition. [As defined in IRCC’s Policy Playbook on Automation]

 

Automated decision support system: Includes any information technology designed to directly support a human decision-maker on an administrative decision (for example, by providing a recommendation), and/or designed to make an administrative decision in lieu of a human decision-maker. This includes systems like eTA or Visitor Record and Study Permit Extension automation in GCMS. [As defined in IRCC’s Policy Playbook on Automation]

 

Black Box: Opaque software tools working outside the scope of meaningful scrutiny and accountability. Usually deep learning systems. Their behaviour can be difficult to interpret and explain, raising concerns over explainability, transparency, and human control. [As defined in IRCC’s Policy Playbook on Automation]

 

Deep learning/neural network is a subset of machine learning, which is essentially a neural network with three or more layers. These neural networks attempt to simulate the behavior of the human brain—albeit far from matching its ability—allowing it to “learn” from large amounts of data. While a neural network with a single layer can still make approximate predictions, additional hidden layers can help to optimize and refine for accuracy. [As defined by IBM: https://www.ibm.com/cloud/learn/deep-learning#:~:text=Deep%20learning%20is%20a%20subset,from%20large%20amounts%20of%20data

 

Exploration zone: The exploration zone – also referred to as a “sandbox” – is the environment used for
research, experimentation and testing related to advanced analytics and Al. Data, codes and software
are isolated from those in production so that they can be tested securely.
“Fettering” of a decision-maker’s discretion: Fettering occurs when a decision-maker does not
genuinely exercise independent judgment in a matter. This can occur when a decision-maker binds
him/herself to a fixed rule of policy, another person’s opinion, or the outputs of a decision support
system. Although an administrative decision-maker may properly be influenced by policy considerations
and other factors, he or she must put his or her mind to the specific circumstances of the case and not
focus blindly on one input (e.g. a risk score provided by an algorithmic system) to the exclusion of other
relevant factors. [As defined in IRCC’s Policy Playbook on Automation]

 

“Fettering” of a decision-maker’s discretion: Fettering occurs when a decision-maker does not
genuinely exercise independent judgment in a matter. This can occur when a decision-maker binds
him/herself to a fixed rule of policy, another person’s opinion, or the outputs of a decision support
system. Although an administrative decision-maker may properly be influenced by policy considerations
and other factors, he or she must put his or her mind to the specific circumstances of the case and not
focus blindly on one input (e.g. a risk score provided by an algorithmic system) to the exclusion of other
relevant factors. [As defined in IRCC’s Policy Playbook on Automation]

 

Machine learning: A sub-category of artificial intelligence, machine learning refers to algorithms and statistical models that learn and improve from examples, data, and experience, rather than following pre-programmed rules. Machine learning systems effectively perform a specific task without using explicit instructions, relying on models and inference instead. [As defined in IRCC’s Policy Playbook on Automation]

 

A minimum viable product (MVP) is a development technique in which a new product or website is developed with sufficient features to satisfy early adopters. The final, complete set of features is only designed and developed after considering feedback from the product’s initial users. [As defined by Techopedia – https://www.techopedia.com/definition/27809/minimum-viable-product-mvp

 

Predictive Analytics: brings together advanced analytics capabilities spanning ad-hoc statistical analysis, predictive modeling, data mining, text analysis, optimization, real-time scoring and machine learning. These tools help organizations discover patterns in data and go beyond knowing what has happened to anticipating what is likely to happen next. [As defined in IRCC’s China-Advanced Analytics TRV Privacy Impact Assessment]

 

Prescriptive Analytics: Prescriptive Analytics is an advanced analytics technology that can provide recommendations to decision-makers and help them achieve business goals by solving complicated optimization problems. [As defined in IRCC’s China-Advanced Analytics TRV Privacy Impact Assessment]

 

Process automation: Also called “business automation” (and sometimes even “digital transformation”), process automation is the use of digital technology to perform routine business processes in a workflow. Process automation can streamline a business for simplicity and improve productivity by taking mundane repetitive tasks from humans and giving them to machines that can do them faster. A wide variety of activities can be automated, or more often, partially automated, with human intervention maintained at strategic points within workflows. In the domain of administrative decision-making at IRCC, “process automation” is used in contrast with “automated decision support,” the former referring to straightforward administrative tasks and the latter reserved for activities involving some degree of judgment. [As defined in IRCC’s Policy Playbook on Automation]

[Last Updated: 19 April 2022 – we will continue to update as new terms get updated]

 

 

 

 

 

 

 

 

Read More »

Why the Need for Permissive Conditions Adds Unnecessary Burden for Canadian International Students

Context of the Problem – Unclear Instructions

In March 2022, IRCC amended the study permit instructions for Study Permits: Working on Campus to add clarity to ability to work without a work permit while as a student.

Unfortunately, because of the nature of the oversimplification of how R.186(f) IRPR is presented in the instructions and as well as the obligation to obtain permissive conditions one one’s study permits allowing for the ability to work, this creates a major problem for international students.

For reference, R.186(f) is quoted below:

No permit required

 A foreign national may work in Canada without a work permit

  • (f) if they are a full-time student, on the campus of the university or college at which they are a full-time student, for the period for which they hold a study permit to study at that university or college;

Rather than the need for permissive conditions, conditions which as of right now are not uniformly understood or applied by decision-makers in granting study permits (let alone CBSA border officers when printing them) I believe we should ideally be operating where only the absence of restrictive conditions is needed.

This is of course the old way things have been done, where students who are not able to work while studying (perhaps those who have been approved to study only part-time or in ESL programs) are restricted and need to apply to amend their study permits by way of a new extension applicatoin.

Consequentially, as a result of these policy changes, a student without this language (perhaps in a final semester where they are exempt from the need to be in full-time studies to work part-time) has to apply to IRCC to change conditions of their study permit. This process at least takes a few months if not more, if other issues were to arise or concerns flagged, not related to the change request. All of this additional labour is needed, because of the lack of permissive conditions. Given IRCC has just changed this (with apparently no reference to the way things used to be done), this will create unnecessary further backlogs and apply retrospectively to confuse both potential employers and students affected.

Importantly, risk adverse educational institutions are already considering restricting students from being able to work without this language on their study permits. This jeopardizes many students who rely on the ability to work 20 hours to perform tasks as a teaching assistant/research assistant or who wish to levy their experiences in their final semester – by taking a part time job, pending graduation/PGWP application.

Not to mention not all students in Canada are working under the authority of R.186(f) IRPR. On strict interpretation, this is what IRCC is making it appear as – but many will be working on the basis of R. 186(u) – on implied status, or even R. 186(p), (v) or (w) IRPR.

For reference below:

  • (p) as a student in a health field, including as a medical elective or clinical clerk at a medical teaching institution in Canada, for the primary purpose of acquiring training, if they have written approval from the body that regulates that field;

  • (u) until a decision is made on an application made by them under subsection 201(1), if they have remained in Canada after the expiry of their work permit and they have continued to comply with the conditions set out on the expired work permit, other than the expiry date;

  • (v) if they are the holder of a study permit and

    • (i) they are a full-time student enrolled at a designated learning institution as defined in section 211.1,

    • (ii) the program in which they are enrolled is a post-secondary academic, vocational or professional training program, or a vocational training program at the secondary level offered in Quebec, in each case, of a duration of six months or more that leads to a degree, diploma or certificate, and

    • (iii) although they are permitted to engage in full-time work during a regularly scheduled break between academic sessions, they work no more than 20 hours per week during a regular academic session;

Indeed, and more specifically, R.186(v) (iii) for final semester exemption seems to tie directly to the implied nature of R.186(f), but arguably now requires that language because of – again – the change to a required permissive condition. 

If this seems confusing to us as practitioners, imagine an on-campus employer who is concerned about hiring an international student without authorization. This has the further impact of stigmatizing international students in the hiring process. From my perspective, the Regs should override the lack of permissive conditions, but for Employers who are looking at websites only for policy guidance, that may not be abundantly clear.

Interim Solution : Make it Easier – Issue a Letter via Automated Portal

While I believe this issue can be made easier, by reverting to the negative/not positive Issue an automatic letter via the new Client Application Portal upon request (i.e. ASAP) where a student shows they are either a full-time student or are exempt for final semester.

Interim Solution 2: Clarify that R. 186(v) and (w) work different and don’t need this permissive language

It is clearly an error in law to suggest that all work needs to be permitted by R. 186(f) IRPR. The instructions should reflect this and exempt either the R.186(v) and (w) IRPR work. If all these need to be permitted by permissive language, I think you are turning a border officer into a detail-oriented immigration officer, and more problems will arise where some receive and some do not receive this condition

 

Ultimate Solution: Standardize Permissions to Be Only Permissive or Only Restrictive and Not a Mix

Between the system changes, I believe IRCC will need to make a choice: either make it permissive and make it standard practice (not subject to error) to have the permissive conditions printed OR (and as I prefer) specifically exclude those who are not eligible on a case-by-case basis and not throw all the responsibility onto study permit holders to do the work correcting errors while being harmed by the waiting period. As great as the Ask or Update Your Application portal is, I am sure the volume of requests will eventually impact it also.

There’s no reasons, in my mind, we need to have permissive and restrictive conditions mixing and blurring the lines of the Regulations. So few students are even being admitted these days for language courses and part-time studies, and those that are – from my perspective – are a much easier group to manage restrictions for then to impact 98% of folks by requiring permissive conditions.

Read More »

A Closer Look at How IRCC’s Officer and Model Rules Advanced Analytics Triage Works

As IRCC ramps up to bring in advanced analytics to all their Lines of Business (LOBs), it is important to take a closer look at what the foundational model, the China TRV Application Process, looks like. Indeed, we know that this TRV model will be the TRV model for the rest of the world sometime this year (if not already).

While this chart is from a few years back, reflecting as I have discussed in many recent presentations and podcasts, how behind we are in this area, my understanding that this three Tier system is still the model in place

Over the next few posts, I’ll try and break down the model in more detail.

This first post will serve as an overview to the process.

I have included a helpful chart, explaining how an application goes from intake to decision made and passport request.

While I will have blog posts, that go into more detail about what ‘Officer Rules’ and ‘Model Rules’ are, here is the basic gist of it. A reminder it only represents the process to approval NOT refusal, and such a similar chart was not provided.

Step 1) Officer’s Rules Extract Applications Out Based on Visa Office-Specific Rules

Each Visa Office has it’s own Officer’s Rules. If an application triggers one of those rules, it no longer gets processed via the Advanced Algorithm/AI model. Think about it as a first filter, likely for those complex files that need a closer look at by IRCC.

You will recall in our discussion of Chinook, the presence of “local word flags” and “risk indicators.” There is no evidence I have yet which links these two pieces together, but presumably the Officer Rules must also be triggered by certain words and flags.

Other than this, we are uncertain about what Officer’s Rules are and we should not expect to know. However, we do know that the SOPs (Standard Operating Procedures) at each Visa Office then apply, rather than the AA/AI model. What it suggests is that the SOPs (and access to these documents) may have the trigger for the word flags.

Step 2) Application of Model Rules

This is where the AA/AI kick in. Model Rules (which I will discuss in a future blog post) are created by IRCC data experts to replicate a high confidence ability to separate applications into Tiers. Tier 1 are the applications that to a high level of confidence, should lead the Applicant to obtain positive eligibility findings. Indeed, Tier 1 Applications are decided with no human in the loop but the computer system will approve them. If the Application is likely to fail the eligibility process, and lead to negative outcomes, it goes to Tier 3. Tier 3 requires Officer review, and – unsurprisingly – has the highest refusal rate as we have discussed in this previous piece.

It is those files that are between positive and negative (the ‘maybe files’) and also the ones that do not fit in the Model Rules nor Officer Rules that become Tier 2. Officers also have to review these cases, but the approval rates are better than Tier 3.

3) Quality Assurance

The Quality Assurance portion of this model, has 10% of all files, filtered to Tier 2 to verify the accuracy of the model.

The models themselves become ‘production models’ when a high level of confidence is met, and they are finalize – such as the ones we have seen for China TRV, India TRV, we believe also China and India Study Permits, but also likely cases such as VESPA (yet this part has not been confirmed). Before it becomes a Production Model, it is in the Exploratory model zone.

How do we know there is a high QA? Well this is where we look at the scoring of the file.

I will break down (and frankly need more research) into this particular model later and it will be the subject of a later piece, but applications are scored to ensure the model is working effectively.

It is interesting that Chinook also has a QA function (and a whole QA Chinook module 6), so it appears there’s even more overlap between the two systems, probably akin to a front-end/back-end type relationship.

4) Pre-Assessment

Tier 1 applications go straight to admissibility review, but those in 2 and 3 go to pre-assessment review by a Clerk.

Important to note here and in the module that these clerks and officers appear to be citing in CPC-O, not the local visa offices abroad. This may also explain why so many more decisions are being made by Canadian decision-makers, even though it may be ultimately delivered or associated with a primary visa office abroad.

But here-in lies a bit of our confusion.

Based on a 2018 ATIP we did, we know that they are triaging different of cases based on case types into “Bins” so certain officers or at least certain lettered numbers – would handle like cases. Yet, this appears to have been the India model then, but the China TRV model seems to centralize it more in Ottawa. Where does the local knowledge and expertise come in? Are there alternative models now that send the decisions to the local visa office or is it only Officer’s rules? Is this perhaps why decisions rendered on the TRVs from India and China are lacking the actual local knowledge that we used to see in decisions because they have been taken outside of the hands of those individuals.

Much of the work locally used to be done on verifying employers, confirming certain elements, but is that now just for those files that are taken out of the triage and flagged as being possible admissibility concerns? Much to think about here.

Again, note that Chinook as a pre-assessment module also that seems to be responsible for many of the same things, so perhaps Chinook is also responsible for presenting the results of that analysis in a more Officer friendly way but why is it also directing the pre-assessment, if it is being done by officers?

5) Eligibility Assessment

What is important to note that this stage is Eligibility where there is no automated approval is still being done by Officers. What we do not know is if there is any guidance directed at Officers to approve/refuse a certain number of Tier 2 or Tier 3 applicants. This information would be crucial. We also know IRCC is trying to automate refusals, so we need to track carefully what that might look like down the road as it intersects with negative eligibility assessments.

6) Admissibility Review + Admissibility Hits

While this likely will be the last portion to be automated, given the need to cross-verify many different sources we also know that IRCC has programs in place such as Watchtower, again the Risk Flags, which may or may not trigger admissibility review. Interestingly enough, even cases where it seems admissibility (misrep) may be at play, it seems to also lead to eligibility refusals or concerns. I would be interested in knowing whether the flagging system also occurs as the eligibility level or whether there is a feedback/pushback system so a decision can be re-routed to eligibility (on an A16 IRPA issue for example).

KEY: Refusals Not Reflected in Chart

What does the refusal system look like? This becomes another key question as decisions are often skipping even the biometrics or verifications and going straight to refusal. This chart obviously would look much more complicated, with probably many more steps at which a refusal can be rendered without having to complete the full eligibility assessment.

Is there a similar map? Can we get access to it?

 

Conclusion – we know nothing yet, but this also changes everything

This model, and this idea of an application being taken out of the assembly line at various places, going through different systems of assessment, really in my mind suggest that we as applicant’s counsel know very little about how our applications will be processed in the future. These systems do not support cookie cutter lawyering, suggest flags may be out of our control and knowledge, and ultimately lead us to question what and who makes up a perfect Tier 1 application.

Models like this also give credence to IRCC’s determination to keep things private and to keep the algorithms and code away from prying investigators and researchers, and ultimately those who may want to take advantage of systems.

Yet, the lack of transparency and concerns that we have about how these systems filter and sort appear very founded. Chinook mirrors much of what is in the AA model. We have our homework cut out for us.

Read More »

Three Belated Crystal Ball Predictions for Canadian Immigration in 2022

While March may seem for some a little late to be predicting a year’s events (given Q1 is nearing it’s end), I will take a contrarian position that is not. Right now is perhaps the perfect time to try and make a prediction. All the big picture pieces are out of the way. We know what the levels plan looks like, especially in terms of the reduction of CECs landed in 2022.

Prediction 1: 2022 will be about AI vs. IA

I believe IRCC is full throttle trying to implement AI (Advanced Analytics) across all their Lines of Business (LOBs), from temporary to permanent residence to citizenship. The speed by which artificial intelligence can be implemented with public support to process high volume of applications to Canada will be pitted against the impact of international affairs/crises/refugee producing situation.  If Ukraine is the new precedent set by IRCC to tackle refugee/humanitarian wars and crises, which politically appears it will have to be – so that the Government can appear anti-racist (see prediction 3), this will inevitably delay/shift resources. If AI can be quickly implemented to deal with the quick decisions (both approvals/refusals) this might be the best solution for the Government. Meanwhile those who are more critical of AI systems (myself included) might ask for more caution in the process;

Email headings between senior A2SC (Advanced Analytics) folks, received via ATIP

 

Prediction 2: TEERing Up the Economic Immigration System Will Leave Some Behind 

The new TEER system replaces NOC in a year where economic permanent resident applications, largely filled by NOC B positions, are backlogged and paused. How will IRCC adapt and change the rules of the game, with the implementation of TEER. What does this mean for the future of FSW/CEC?

If the math is as it is above, we could see a shrinking of NOC 0AB so that that the 70% of unit groups once eligible (NOC 0, A,B) turns into 59% (Tier 0, 1, 2). While it seems like a lot of what will occur will be ‘mergers’, I am eager to see what happens to tweener jobs such as administrative assistant and retail sales supervisor. I suspect, the first place we will see a major impact will be in the Federal Skilled Worker where we may move to exclusion lists or targeted draws for specific TEER categories.

 

Prediction 3: IRCC will be forced/asked to clean up the house on anti-racismIRCC’s Anti-Racism Polaris Report and recent concerns (including the next Parliamentary Study) about discrepant processing rates will lead the Department to try and address this in policy options and offerings.

The emails between IRCC staff looking into preventing bias and anti-racism in systems is good work in the right direction, but growing calls will be for an independent oversight commission or ombudsperson.

Immigration is so deeply entrenched with racist roots from our history of exclusion, now manifested in explicit and implicit biases, two tiered systems, secret programs, and different criteria, that I really do not see how we can build an anti-racist system without first tearing down the first one. Economically (in terms of investment into things such as technology) and politically (given we are still considered globally to have a decent/attractive system), I don’t see us doing that.

What you will likely see is a greater platforming and emphasis of the Gender Based Analysis (GBA+) work as well as projects taken up that give at least a cover or presentation of progress. Yet, myself and other critiques are still hopeful that the Government does not shy away from a hard, introspective, look at the systems that have already been developed and paid for to see where key fixes are needed.

I do see that those on the other side, advocates, lawyers, etc. are shifting away from their own Whiteness and once those litigation skills and experiences are transferred to the new generation of racialized lawyers who have a keen sense of justice and have lived/feel the discrepancy, they will start attacking the foundations. I think right now is the perfect time for IRCC to do some public relations/communication work around anti-racism, to pad the intention piece, and build in justifications/explanations/evidence for when these matters eventually get litigated.

As I have presented and said – immigration is itself state-sponsored discrimination. I don’t think we will ever eliminate it to a point where Applicants are happy and Immigration loses its role as a filtering mechanism based on race + citizenship, as a defining feature. Yet, I definitely see a bigger role for those who advocate for safeguards and 2022 as the year some of those safeguards start being introduced.

Read More »
About Us
Will Tao is an Award-Winning Canadian Immigration and Refugee Lawyer, Writer, and Policy Advisor based in Vancouver. Vancouver Immigration Blog is a public legal resource and social commentary.

Let’s Get in Touch

Translate »